Overview

Dataset statistics

Number of variables65
Number of observations70406
Missing cells2755022
Missing cells (%)60.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.9 MiB
Average record size in memory520.0 B

Variable types

Categorical47
Unsupported4
Numeric10
Boolean4

Alerts

LPG Primary has constant value "True"Constant
Hydrogen Is Retail has constant value "True"Constant
LNG On-Site Renewable Source has constant value "NONE"Constant
LNG Vehicle Class has constant value "HD"Constant
Station Name has a high cardinality: 62835 distinct valuesHigh cardinality
Street Address has a high cardinality: 52295 distinct valuesHigh cardinality
Intersection Directions has a high cardinality: 4034 distinct valuesHigh cardinality
City has a high cardinality: 8278 distinct valuesHigh cardinality
State has a high cardinality: 65 distinct valuesHigh cardinality
Station Phone has a high cardinality: 17059 distinct valuesHigh cardinality
Expected Date has a high cardinality: 145 distinct valuesHigh cardinality
Access Days Time has a high cardinality: 2552 distinct valuesHigh cardinality
Cards Accepted has a high cardinality: 728 distinct valuesHigh cardinality
Date Last Confirmed has a high cardinality: 92 distinct valuesHigh cardinality
Updated At has a high cardinality: 4816 distinct valuesHigh cardinality
Open Date has a high cardinality: 3796 distinct valuesHigh cardinality
Hydrogen Status Link has a high cardinality: 82 distinct valuesHigh cardinality
Intersection Directions (French) has a high cardinality: 172 distinct valuesHigh cardinality
Access Days Time (French) has a high cardinality: 755 distinct valuesHigh cardinality
Facility Type has a high cardinality: 62 distinct valuesHigh cardinality
EV Pricing has a high cardinality: 749 distinct valuesHigh cardinality
EV Pricing (French) has a high cardinality: 140 distinct valuesHigh cardinality
Fuel Type Code is highly imbalanced (70.2%)Imbalance
Station Phone is highly imbalanced (52.5%)Imbalance
Status Code is highly imbalanced (91.3%)Imbalance
Groups With Access Code is highly imbalanced (76.3%)Imbalance
Access Days Time is highly imbalanced (73.1%)Imbalance
BD Blends is highly imbalanced (68.8%)Imbalance
EV Network Web is highly imbalanced (50.5%)Imbalance
Geocode Status is highly imbalanced (62.5%)Imbalance
Date Last Confirmed is highly imbalanced (51.7%)Imbalance
Owner Type Code is highly imbalanced (65.2%)Imbalance
NG Vehicle Class is highly imbalanced (53.8%)Imbalance
EV Connector Types is highly imbalanced (72.4%)Imbalance
Access Days Time (French) is highly imbalanced (64.3%)Imbalance
Groups With Access Code (French) is highly imbalanced (76.3%)Imbalance
Access Code is highly imbalanced (62.6%)Imbalance
CNG On-Site Renewable Source is highly imbalanced (90.0%)Imbalance
E85 Other Ethanol Blends is highly imbalanced (63.1%)Imbalance
EV Pricing is highly imbalanced (66.9%)Imbalance
EV Pricing (French) is highly imbalanced (69.6%)Imbalance
Hydrogen Standards is highly imbalanced (92.8%)Imbalance
CNG Vehicle Class is highly imbalanced (51.0%)Imbalance
Restricted Access is highly imbalanced (84.0%)Imbalance
Intersection Directions has 65914 (93.6%) missing valuesMissing
Plus4 has 70406 (100.0%) missing valuesMissing
Station Phone has 5202 (7.4%) missing valuesMissing
Expected Date has 69188 (98.3%) missing valuesMissing
Access Days Time has 3778 (5.4%) missing valuesMissing
Cards Accepted has 59117 (84.0%) missing valuesMissing
BD Blends has 69189 (98.3%) missing valuesMissing
NG Fill Type Code has 68803 (97.7%) missing valuesMissing
NG PSI has 68809 (97.7%) missing valuesMissing
EV Level1 EVSE Num has 70120 (99.6%) missing valuesMissing
EV Level2 EVSE Num has 16262 (23.1%) missing valuesMissing
EV DC Fast Count has 62099 (88.2%) missing valuesMissing
EV Other Info has 70357 (99.9%) missing valuesMissing
EV Network has 9499 (13.5%) missing valuesMissing
EV Network Web has 20101 (28.6%) missing valuesMissing
Owner Type Code has 40216 (57.1%) missing valuesMissing
Federal Agency ID has 69451 (98.6%) missing valuesMissing
Federal Agency Name has 69451 (98.6%) missing valuesMissing
Open Date has 1096 (1.6%) missing valuesMissing
Hydrogen Status Link has 70323 (99.9%) missing valuesMissing
NG Vehicle Class has 68626 (97.5%) missing valuesMissing
LPG Primary has 68539 (97.3%) missing valuesMissing
E85 Blender Pump has 65898 (93.6%) missing valuesMissing
EV Connector Types has 9716 (13.8%) missing valuesMissing
Intersection Directions (French) has 70218 (99.7%) missing valuesMissing
Access Days Time (French) has 63815 (90.6%) missing valuesMissing
BD Blends (French) has 70404 (> 99.9%) missing valuesMissing
Hydrogen Is Retail has 70289 (99.8%) missing valuesMissing
Access Detail Code has 62983 (89.5%) missing valuesMissing
Federal Agency Code has 69451 (98.6%) missing valuesMissing
Facility Type has 42741 (60.7%) missing valuesMissing
CNG Dispenser Num has 69367 (98.5%) missing valuesMissing
CNG On-Site Renewable Source has 69690 (99.0%) missing valuesMissing
CNG Total Compression Capacity has 69698 (99.0%) missing valuesMissing
CNG Storage Capacity has 70049 (99.5%) missing valuesMissing
LNG On-Site Renewable Source has 70344 (99.9%) missing valuesMissing
E85 Other Ethanol Blends has 68948 (97.9%) missing valuesMissing
EV Pricing has 53445 (75.9%) missing valuesMissing
EV Pricing (French) has 68374 (97.1%) missing valuesMissing
LPG Nozzle Types has 68580 (97.4%) missing valuesMissing
Hydrogen Pressures has 70290 (99.8%) missing valuesMissing
Hydrogen Standards has 70290 (99.8%) missing valuesMissing
CNG Fill Type Code has 68803 (97.7%) missing valuesMissing
CNG PSI has 68809 (97.7%) missing valuesMissing
CNG Vehicle Class has 68784 (97.7%) missing valuesMissing
LNG Vehicle Class has 70248 (99.8%) missing valuesMissing
EV On-Site Renewable Source has 70036 (99.5%) missing valuesMissing
Restricted Access has 16971 (24.1%) missing valuesMissing
EV Level2 EVSE Num is highly skewed (γ1 = 29.92238224)Skewed
Intersection Directions is uniformly distributedUniform
Hydrogen Status Link is uniformly distributedUniform
Intersection Directions (French) is uniformly distributedUniform
BD Blends (French) is uniformly distributedUniform
ID has unique valuesUnique
ZIP is an unsupported type, check if it needs cleaning or further analysisUnsupported
Plus4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
NG PSI is an unsupported type, check if it needs cleaning or further analysisUnsupported
CNG PSI is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-08-29 04:24:56.967369
Analysis finished2023-08-29 04:25:47.283758
Duration50.32 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

Fuel Type Code
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
ELEC
60907 
E85
 
4508
LPG
 
1867
CNG
 
1631
BD
 
1218
Other values (2)
 
275

Length

Max length4
Median length4
Mean length3.8461211
Min length2

Characters and Unicode

Total characters270790
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCNG
2nd rowCNG
3rd rowCNG
4th rowCNG
5th rowCNG

Common Values

ValueCountFrequency (%)
ELEC 60907
86.5%
E85 4508
 
6.4%
LPG 1867
 
2.7%
CNG 1631
 
2.3%
BD 1218
 
1.7%
LNG 158
 
0.2%
HY 117
 
0.2%

Length

2023-08-29T04:25:47.586141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:25:47.998893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
elec 60907
86.5%
e85 4508
 
6.4%
lpg 1867
 
2.7%
cng 1631
 
2.3%
bd 1218
 
1.7%
lng 158
 
0.2%
hy 117
 
0.2%

Most occurring characters

ValueCountFrequency (%)
E 126322
46.6%
L 62932
23.2%
C 62538
23.1%
8 4508
 
1.7%
5 4508
 
1.7%
G 3656
 
1.4%
P 1867
 
0.7%
N 1789
 
0.7%
B 1218
 
0.4%
D 1218
 
0.4%
Other values (2) 234
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 261774
96.7%
Decimal Number 9016
 
3.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 126322
48.3%
L 62932
24.0%
C 62538
23.9%
G 3656
 
1.4%
P 1867
 
0.7%
N 1789
 
0.7%
B 1218
 
0.5%
D 1218
 
0.5%
H 117
 
< 0.1%
Y 117
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
8 4508
50.0%
5 4508
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 261774
96.7%
Common 9016
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 126322
48.3%
L 62932
24.0%
C 62538
23.9%
G 3656
 
1.4%
P 1867
 
0.7%
N 1789
 
0.7%
B 1218
 
0.5%
D 1218
 
0.5%
H 117
 
< 0.1%
Y 117
 
< 0.1%
Common
ValueCountFrequency (%)
8 4508
50.0%
5 4508
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 270790
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 126322
46.6%
L 62932
23.2%
C 62538
23.1%
8 4508
 
1.7%
5 4508
 
1.7%
G 3656
 
1.4%
P 1867
 
0.7%
N 1789
 
0.7%
B 1218
 
0.4%
D 1218
 
0.4%
Other values (2) 234
 
0.1%

Station Name
Categorical

Distinct62835
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
Casey's General Store
 
935
U-Haul
 
551
Sheetz
 
102
Wawa - Tesla Supercharger
 
88
Swtch Energy
 
78
Other values (62830)
68652 

Length

Max length116
Median length84
Mean length24.539116
Min length2

Characters and Unicode

Total characters1727701
Distinct characters115
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60377 ?
Unique (%)85.8%

Sample

1st rowSpire - Montgomery Operations Center
2nd rowPS Energy - Atlanta
3rd rowMetropolitan Atlanta Rapid Transit Authority
4th rowUnited Parcel Service
5th rowArkansas Oklahoma Gas Corp

Common Values

ValueCountFrequency (%)
Casey's General Store 935
 
1.3%
U-Haul 551
 
0.8%
Sheetz 102
 
0.1%
Wawa - Tesla Supercharger 88
 
0.1%
Swtch Energy 78
 
0.1%
United Parcel Service 74
 
0.1%
Shell 65
 
0.1%
Sheetz - Tesla Supercharger 62
 
0.1%
Petro-Canada 59
 
0.1%
RaceTrac 57
 
0.1%
Other values (62825) 68335
97.1%

Length

2023-08-29T04:25:48.707575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
19276
 
6.6%
tesla 6529
 
2.2%
1 5646
 
1.9%
station 5504
 
1.9%
destination 4902
 
1.7%
2 3889
 
1.3%
of 3463
 
1.2%
city 2921
 
1.0%
center 2404
 
0.8%
the 1756
 
0.6%
Other values (32412) 236891
80.8%

Most occurring characters

ValueCountFrequency (%)
224142
 
13.0%
e 95618
 
5.5%
a 78713
 
4.6%
n 64143
 
3.7%
r 60941
 
3.5%
t 60518
 
3.5%
i 58000
 
3.4%
o 57660
 
3.3%
T 55194
 
3.2%
A 54485
 
3.2%
Other values (105) 918287
53.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 726674
42.1%
Uppercase Letter 652375
37.8%
Space Separator 224146
 
13.0%
Decimal Number 80834
 
4.7%
Dash Punctuation 26139
 
1.5%
Other Punctuation 15333
 
0.9%
Open Punctuation 813
 
< 0.1%
Close Punctuation 804
 
< 0.1%
Connector Punctuation 403
 
< 0.1%
Final Punctuation 103
 
< 0.1%
Other values (5) 77
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 95618
13.2%
a 78713
10.8%
n 64143
8.8%
r 60941
8.4%
t 60518
8.3%
i 58000
8.0%
o 57660
7.9%
s 46626
 
6.4%
l 44668
 
6.1%
u 20636
 
2.8%
Other values (29) 139151
19.1%
Uppercase Letter
ValueCountFrequency (%)
T 55194
 
8.5%
A 54485
 
8.4%
S 51333
 
7.9%
E 49267
 
7.6%
C 48242
 
7.4%
O 41184
 
6.3%
R 39995
 
6.1%
N 37046
 
5.7%
I 34069
 
5.2%
L 31917
 
4.9%
Other values (23) 209643
32.1%
Other Punctuation
ValueCountFrequency (%)
# 5391
35.2%
& 2642
17.2%
' 2434
15.9%
. 1676
 
10.9%
, 1495
 
9.8%
@ 1022
 
6.7%
/ 449
 
2.9%
: 159
 
1.0%
; 27
 
0.2%
! 19
 
0.1%
Other values (3) 19
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 19597
24.2%
2 13852
17.1%
0 10898
13.5%
3 8023
9.9%
5 6657
 
8.2%
4 6547
 
8.1%
6 4751
 
5.9%
7 3930
 
4.9%
8 3317
 
4.1%
9 3262
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 26093
99.8%
44
 
0.2%
2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 805
99.0%
[ 7
 
0.9%
1
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 57
80.3%
| 12
 
16.9%
= 2
 
2.8%
Space Separator
ValueCountFrequency (%)
224142
> 99.9%
  4
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 797
99.1%
] 7
 
0.9%
Modifier Symbol
ValueCountFrequency (%)
´ 1
50.0%
` 1
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 403
100.0%
Final Punctuation
ValueCountFrequency (%)
103
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1379049
79.8%
Common 348652
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 95618
 
6.9%
a 78713
 
5.7%
n 64143
 
4.7%
r 60941
 
4.4%
t 60518
 
4.4%
i 58000
 
4.2%
o 57660
 
4.2%
T 55194
 
4.0%
A 54485
 
4.0%
S 51333
 
3.7%
Other values (62) 742444
53.8%
Common
ValueCountFrequency (%)
224142
64.3%
- 26093
 
7.5%
1 19597
 
5.6%
2 13852
 
4.0%
0 10898
 
3.1%
3 8023
 
2.3%
5 6657
 
1.9%
4 6547
 
1.9%
# 5391
 
1.5%
6 4751
 
1.4%
Other values (33) 22701
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1726181
99.9%
None 1368
 
0.1%
Punctuation 150
 
< 0.1%
Modifier Letters 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
224142
 
13.0%
e 95618
 
5.5%
a 78713
 
4.6%
n 64143
 
3.7%
r 60941
 
3.5%
t 60518
 
3.5%
i 58000
 
3.4%
o 57660
 
3.3%
T 55194
 
3.2%
A 54485
 
3.2%
Other values (77) 916767
53.1%
None
ValueCountFrequency (%)
é 787
57.5%
è 179
 
13.1%
É 179
 
13.1%
ô 151
 
11.0%
â 21
 
1.5%
ç 7
 
0.5%
Î 7
 
0.5%
à 6
 
0.4%
î 5
 
0.4%
  4
 
0.3%
Other values (13) 22
 
1.6%
Punctuation
ValueCountFrequency (%)
103
68.7%
44
29.3%
2
 
1.3%
1
 
0.7%
Modifier Letters
ValueCountFrequency (%)
ʻ 2
100.0%

Street Address
Categorical

Distinct52295
Distinct (%)74.3%
Missing1
Missing (%)< 0.1%
Memory size550.2 KiB
5515 Overland Ave
 
118
1201 Pine St
 
81
2910 Tannery Way
 
79
1 Facebook Way
 
61
Unnamed Road
 
59
Other values (52290)
70007 

Length

Max length76
Median length63
Mean length17.485789
Min length3

Characters and Unicode

Total characters1231087
Distinct characters101
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43384 ?
Unique (%)61.6%

Sample

1st row2951 Chestnut St
2nd row340 Whitehall St
3rd row2424 Piedmont Rd NE
4th row270 Marvin Miller Dr
5th row2100 S Waldron Rd

Common Values

ValueCountFrequency (%)
5515 Overland Ave 118
 
0.2%
1201 Pine St 81
 
0.1%
2910 Tannery Way 79
 
0.1%
1 Facebook Way 61
 
0.1%
Unnamed Road 59
 
0.1%
806 S Airport Blvd Long Term Garage 2 57
 
0.1%
3162 Olin Ave 49
 
0.1%
150 W Tasman Dr 40
 
0.1%
309 Constitution Dr 36
 
0.1%
2595 Augustine Dr 34
 
< 0.1%
Other values (52285) 69791
99.1%

Length

2023-08-29T04:25:49.444570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
st 15331
 
6.0%
ave 10157
 
4.0%
rd 9889
 
3.9%
dr 6280
 
2.5%
blvd 5319
 
2.1%
w 4735
 
1.9%
s 4661
 
1.8%
n 4641
 
1.8%
e 4512
 
1.8%
street 2007
 
0.8%
Other values (24758) 187455
73.5%

Most occurring characters

ValueCountFrequency (%)
184967
 
15.0%
e 75025
 
6.1%
a 56985
 
4.6%
t 54635
 
4.4%
r 52347
 
4.3%
0 51362
 
4.2%
1 51107
 
4.2%
n 43511
 
3.5%
o 38959
 
3.2%
i 37054
 
3.0%
Other values (91) 585135
47.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 587099
47.7%
Decimal Number 267241
21.7%
Space Separator 184967
 
15.0%
Uppercase Letter 182455
 
14.8%
Other Punctuation 5312
 
0.4%
Dash Punctuation 3699
 
0.3%
Control 95
 
< 0.1%
Open Punctuation 94
 
< 0.1%
Close Punctuation 85
 
< 0.1%
Final Punctuation 20
 
< 0.1%
Other values (4) 20
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 75025
12.8%
a 56985
9.7%
t 54635
9.3%
r 52347
 
8.9%
n 43511
 
7.4%
o 38959
 
6.6%
i 37054
 
6.3%
l 36825
 
6.3%
d 32161
 
5.5%
v 23075
 
3.9%
Other values (27) 136522
23.3%
Uppercase Letter
ValueCountFrequency (%)
S 31984
17.5%
A 15845
 
8.7%
R 15754
 
8.6%
W 12613
 
6.9%
C 12222
 
6.7%
B 11828
 
6.5%
D 10280
 
5.6%
N 9384
 
5.1%
E 9258
 
5.1%
P 8965
 
4.9%
Other values (19) 44322
24.3%
Decimal Number
ValueCountFrequency (%)
0 51362
19.2%
1 51107
19.1%
5 30380
11.4%
2 30155
11.3%
3 23472
8.8%
4 19748
 
7.4%
7 16012
 
6.0%
6 15771
 
5.9%
9 14748
 
5.5%
8 14486
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 2790
52.5%
@ 972
 
18.3%
, 726
 
13.7%
' 275
 
5.2%
# 224
 
4.2%
& 215
 
4.0%
/ 64
 
1.2%
; 37
 
0.7%
" 8
 
0.2%
: 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 3691
99.8%
6
 
0.2%
2
 
0.1%
Control
ValueCountFrequency (%)
47
49.5%
47
49.5%
1
 
1.1%
Other Number
ValueCountFrequency (%)
½ 2
66.7%
¼ 1
33.3%
Space Separator
ValueCountFrequency (%)
184967
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Final Punctuation
ValueCountFrequency (%)
20
100.0%
Math Symbol
ValueCountFrequency (%)
+ 15
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 769555
62.5%
Common 461532
37.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 75025
 
9.7%
a 56985
 
7.4%
t 54635
 
7.1%
r 52347
 
6.8%
n 43511
 
5.7%
o 38959
 
5.1%
i 37054
 
4.8%
l 36825
 
4.8%
d 32161
 
4.2%
S 31984
 
4.2%
Other values (57) 310069
40.3%
Common
ValueCountFrequency (%)
184967
40.1%
0 51362
 
11.1%
1 51107
 
11.1%
5 30380
 
6.6%
2 30155
 
6.5%
3 23472
 
5.1%
4 19748
 
4.3%
7 16012
 
3.5%
6 15771
 
3.4%
9 14748
 
3.2%
Other values (24) 23810
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1230474
> 99.9%
None 584
 
< 0.1%
Punctuation 28
 
< 0.1%
Phonetic Ext 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
184967
 
15.0%
e 75025
 
6.1%
a 56985
 
4.6%
t 54635
 
4.4%
r 52347
 
4.3%
0 51362
 
4.2%
1 51107
 
4.2%
n 43511
 
3.5%
o 38959
 
3.2%
i 37054
 
3.0%
Other values (70) 584522
47.5%
None
ValueCountFrequency (%)
é 356
61.0%
è 85
 
14.6%
É 63
 
10.8%
ô 35
 
6.0%
í 15
 
2.6%
ç 8
 
1.4%
ñ 4
 
0.7%
Î 3
 
0.5%
ê 3
 
0.5%
½ 2
 
0.3%
Other values (7) 10
 
1.7%
Punctuation
ValueCountFrequency (%)
20
71.4%
6
 
21.4%
2
 
7.1%
Phonetic Ext
ValueCountFrequency (%)
1
100.0%

Intersection Directions
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct4034
Distinct (%)89.8%
Missing65914
Missing (%)93.6%
Memory size550.2 KiB
.
 
39
LCNG station
 
33
Located in the parking lot
 
11
Roslyn St and E 53rd Place
 
10
Located behind the building
 
7
Other values (4029)
4392 

Length

Max length507
Median length219
Mean length46.990873
Min length2

Characters and Unicode

Total characters211083
Distinct characters90
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3744 ?
Unique (%)83.3%

Sample

1st rowFrom I-7585 N, exit 91 to Central Ave, left on Memorial, left on Whitehall, and the station is on the left
2nd rowFrom Route 1, take the first exit after Callahan Tunnel. Located near the Massachusetts State Police Troop F building on Service Rd.
3rd rowRt 16, exit to Rt 99, to Dexter St to Rover. Or Rt 99 to Robin St, to Rover St
4th rowI-278/Brooklyn Queens Expy, exit onto Vandervoort Ave S, left onto Maspeth Ave, and the station is on the left
5th rowFrom Shore Pkwy, take Rockaway Pkwy N, left onto Ditmas Ave, and station is on the left

Common Values

ValueCountFrequency (%)
. 39
 
0.1%
LCNG station 33
 
< 0.1%
Located in the parking lot 11
 
< 0.1%
Roslyn St and E 53rd Place 10
 
< 0.1%
Located behind the building 7
 
< 0.1%
Parking Lot 7
 
< 0.1%
Attendant will assist in charging vehicle. Parking rates apply. Inquire within. 6
 
< 0.1%
Chargers are under repair. 6
 
< 0.1%
Charger under repair. 6
 
< 0.1%
Located in parking lot 6
 
< 0.1%
Other values (4024) 4361
 
6.2%
(Missing) 65914
93.6%

Length

2023-08-29T04:25:49.940126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the 2207
 
5.7%
of 1756
 
4.6%
and 1126
 
2.9%
located 1123
 
2.9%
on 1037
 
2.7%
parking 900
 
2.3%
at 824
 
2.1%
in 692
 
1.8%
lot 513
 
1.3%
to 498
 
1.3%
Other values (4565) 27799
72.3%

Most occurring characters

ValueCountFrequency (%)
34041
16.1%
e 17245
 
8.2%
t 15514
 
7.3%
a 12918
 
6.1%
o 12590
 
6.0%
n 11982
 
5.7%
r 11040
 
5.2%
i 10038
 
4.8%
s 6980
 
3.3%
l 6097
 
2.9%
Other values (80) 72638
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 144623
68.5%
Space Separator 34041
 
16.1%
Uppercase Letter 16264
 
7.7%
Decimal Number 7871
 
3.7%
Other Punctuation 4247
 
2.0%
Control 2714
 
1.3%
Dash Punctuation 903
 
0.4%
Currency Symbol 143
 
0.1%
Open Punctuation 127
 
0.1%
Close Punctuation 127
 
0.1%
Other values (3) 23
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 17245
11.9%
t 15514
10.7%
a 12918
 
8.9%
o 12590
 
8.7%
n 11982
 
8.3%
r 11040
 
7.6%
i 10038
 
6.9%
s 6980
 
4.8%
l 6097
 
4.2%
d 5989
 
4.1%
Other values (16) 34230
23.7%
Uppercase Letter
ValueCountFrequency (%)
S 1946
 
12.0%
L 1432
 
8.8%
A 1263
 
7.8%
C 1258
 
7.7%
R 993
 
6.1%
E 945
 
5.8%
P 860
 
5.3%
I 824
 
5.1%
N 807
 
5.0%
B 784
 
4.8%
Other values (16) 5152
31.7%
Other Punctuation
ValueCountFrequency (%)
. 2115
49.8%
, 1165
27.4%
/ 265
 
6.2%
& 239
 
5.6%
; 139
 
3.3%
# 131
 
3.1%
: 74
 
1.7%
' 74
 
1.7%
" 15
 
0.4%
* 10
 
0.2%
Other values (3) 20
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 1528
19.4%
0 1155
14.7%
2 1013
12.9%
5 841
10.7%
3 717
9.1%
4 706
9.0%
6 518
 
6.6%
9 493
 
6.3%
7 454
 
5.8%
8 446
 
5.7%
Math Symbol
ValueCountFrequency (%)
| 11
61.1%
~ 3
 
16.7%
= 2
 
11.1%
+ 2
 
11.1%
Control
ValueCountFrequency (%)
1356
50.0%
1356
50.0%
2
 
0.1%
Other Symbol
ValueCountFrequency (%)
🟣 1
50.0%
° 1
50.0%
Space Separator
ValueCountFrequency (%)
34041
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 903
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Final Punctuation
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 160887
76.2%
Common 50196
 
23.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 17245
 
10.7%
t 15514
 
9.6%
a 12918
 
8.0%
o 12590
 
7.8%
n 11982
 
7.4%
r 11040
 
6.9%
i 10038
 
6.2%
s 6980
 
4.3%
l 6097
 
3.8%
d 5989
 
3.7%
Other values (42) 50494
31.4%
Common
ValueCountFrequency (%)
34041
67.8%
. 2115
 
4.2%
1 1528
 
3.0%
1356
 
2.7%
1356
 
2.7%
, 1165
 
2.3%
0 1155
 
2.3%
2 1013
 
2.0%
- 903
 
1.8%
5 841
 
1.7%
Other values (28) 4723
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 211078
> 99.9%
Punctuation 3
 
< 0.1%
Geometric Shapes Ext 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34041
16.1%
e 17245
 
8.2%
t 15514
 
7.3%
a 12918
 
6.1%
o 12590
 
6.0%
n 11982
 
5.7%
r 11040
 
5.2%
i 10038
 
4.8%
s 6980
 
3.3%
l 6097
 
2.9%
Other values (77) 72633
34.4%
Punctuation
ValueCountFrequency (%)
3
100.0%
Geometric Shapes Ext
ValueCountFrequency (%)
🟣 1
100.0%
None
ValueCountFrequency (%)
° 1
100.0%

City
Categorical

Distinct8278
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
Los Angeles
 
1586
San Diego
 
918
Montréal
 
635
Atlanta
 
608
San Jose
 
587
Other values (8273)
66072 

Length

Max length38
Median length31
Mean length9.0480215
Min length2

Characters and Unicode

Total characters637035
Distinct characters89
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3229 ?
Unique (%)4.6%

Sample

1st rowMontgomery
2nd rowAtlanta
3rd rowAtlanta
4th rowAtlanta
5th rowFort Smith

Common Values

ValueCountFrequency (%)
Los Angeles 1586
 
2.3%
San Diego 918
 
1.3%
Montréal 635
 
0.9%
Atlanta 608
 
0.9%
San Jose 587
 
0.8%
Irvine 580
 
0.8%
Austin 579
 
0.8%
Kansas City 463
 
0.7%
San Francisco 453
 
0.6%
Seattle 429
 
0.6%
Other values (8268) 63568
90.3%

Length

2023-08-29T04:25:50.397878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
san 2863
 
3.1%
city 2076
 
2.2%
los 1666
 
1.8%
angeles 1599
 
1.7%
park 1115
 
1.2%
beach 1098
 
1.2%
santa 973
 
1.0%
diego 918
 
1.0%
new 785
 
0.8%
lake 698
 
0.8%
Other values (6891) 79134
85.2%

Most occurring characters

ValueCountFrequency (%)
a 59529
 
9.3%
e 57314
 
9.0%
n 48769
 
7.7%
o 48558
 
7.6%
l 39044
 
6.1%
r 38852
 
6.1%
i 36354
 
5.7%
t 34560
 
5.4%
s 28890
 
4.5%
22520
 
3.5%
Other values (79) 222645
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 516398
81.1%
Uppercase Letter 95334
 
15.0%
Space Separator 22520
 
3.5%
Dash Punctuation 2043
 
0.3%
Other Punctuation 668
 
0.1%
Decimal Number 51
 
< 0.1%
Math Symbol 7
 
< 0.1%
Other Symbol 6
 
< 0.1%
Final Punctuation 4
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 59529
11.5%
e 57314
11.1%
n 48769
9.4%
o 48558
9.4%
l 39044
 
7.6%
r 38852
 
7.5%
i 36354
 
7.0%
t 34560
 
6.7%
s 28890
 
5.6%
u 14817
 
2.9%
Other values (27) 109711
21.2%
Uppercase Letter
ValueCountFrequency (%)
S 11699
12.3%
C 9506
 
10.0%
B 7216
 
7.6%
L 6871
 
7.2%
M 6749
 
7.1%
A 6711
 
7.0%
P 5816
 
6.1%
R 4131
 
4.3%
H 3947
 
4.1%
W 3894
 
4.1%
Other values (18) 28794
30.2%
Decimal Number
ValueCountFrequency (%)
5 8
15.7%
7 8
15.7%
2 7
13.7%
9 6
11.8%
3 6
11.8%
1 5
9.8%
0 4
7.8%
6 3
 
5.9%
4 3
 
5.9%
8 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 532
79.6%
' 121
 
18.1%
, 12
 
1.8%
! 2
 
0.3%
/ 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2039
99.8%
4
 
0.2%
Other Symbol
ValueCountFrequency (%)
© 5
83.3%
® 1
 
16.7%
Space Separator
ValueCountFrequency (%)
22520
100.0%
Math Symbol
ValueCountFrequency (%)
7
100.0%
Final Punctuation
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 611732
96.0%
Common 25303
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 59529
 
9.7%
e 57314
 
9.4%
n 48769
 
8.0%
o 48558
 
7.9%
l 39044
 
6.4%
r 38852
 
6.4%
i 36354
 
5.9%
t 34560
 
5.6%
s 28890
 
4.7%
u 14817
 
2.4%
Other values (55) 205045
33.5%
Common
ValueCountFrequency (%)
22520
89.0%
- 2039
 
8.1%
. 532
 
2.1%
' 121
 
0.5%
, 12
 
< 0.1%
5 8
 
< 0.1%
7 8
 
< 0.1%
7
 
< 0.1%
2 7
 
< 0.1%
9 6
 
< 0.1%
Other values (14) 43
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 635810
99.8%
None 1210
 
0.2%
Punctuation 8
 
< 0.1%
Math Operators 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 59529
 
9.4%
e 57314
 
9.0%
n 48769
 
7.7%
o 48558
 
7.6%
l 39044
 
6.1%
r 38852
 
6.1%
i 36354
 
5.7%
t 34560
 
5.4%
s 28890
 
4.5%
22520
 
3.5%
Other values (61) 221420
34.8%
None
ValueCountFrequency (%)
é 1003
82.9%
è 132
 
10.9%
ô 19
 
1.6%
É 16
 
1.3%
Î 12
 
1.0%
â 6
 
0.5%
© 5
 
0.4%
ç 4
 
0.3%
à 4
 
0.3%
ê 2
 
0.2%
Other values (5) 7
 
0.6%
Math Operators
ValueCountFrequency (%)
7
100.0%
Punctuation
ValueCountFrequency (%)
4
50.0%
4
50.0%

State
Categorical

Distinct65
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
CA
16106 
QC
 
3502
NY
 
3409
FL
 
3113
TX
 
3002
Other values (60)
41274 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters140812
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowAL
2nd rowGA
3rd rowGA
4th rowGA
5th rowAR

Common Values

ValueCountFrequency (%)
CA 16106
22.9%
QC 3502
 
5.0%
NY 3409
 
4.8%
FL 3113
 
4.4%
TX 3002
 
4.3%
ON 2472
 
3.5%
MA 2385
 
3.4%
WA 1916
 
2.7%
CO 1894
 
2.7%
GA 1763
 
2.5%
Other values (55) 30844
43.8%

Length

2023-08-29T04:25:51.255118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ca 16106
22.9%
qc 3502
 
5.0%
ny 3409
 
4.8%
fl 3113
 
4.4%
tx 3002
 
4.3%
on 2472
 
3.5%
ma 2385
 
3.4%
wa 1916
 
2.7%
co 1894
 
2.7%
ga 1763
 
2.5%
Other values (55) 30844
43.8%

Most occurring characters

ValueCountFrequency (%)
A 28650
20.3%
C 25974
18.4%
N 12942
9.2%
M 8852
 
6.3%
O 8669
 
6.2%
I 6359
 
4.5%
T 5828
 
4.1%
L 5445
 
3.9%
Y 3868
 
2.7%
Q 3502
 
2.5%
Other values (16) 30723
21.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 140812
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 28650
20.3%
C 25974
18.4%
N 12942
9.2%
M 8852
 
6.3%
O 8669
 
6.2%
I 6359
 
4.5%
T 5828
 
4.1%
L 5445
 
3.9%
Y 3868
 
2.7%
Q 3502
 
2.5%
Other values (16) 30723
21.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 140812
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 28650
20.3%
C 25974
18.4%
N 12942
9.2%
M 8852
 
6.3%
O 8669
 
6.2%
I 6359
 
4.5%
T 5828
 
4.1%
L 5445
 
3.9%
Y 3868
 
2.7%
Q 3502
 
2.5%
Other values (16) 30723
21.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 140812
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 28650
20.3%
C 25974
18.4%
N 12942
9.2%
M 8852
 
6.3%
O 8669
 
6.2%
I 6359
 
4.5%
T 5828
 
4.1%
L 5445
 
3.9%
Y 3868
 
2.7%
Q 3502
 
2.5%
Other values (16) 30723
21.8%

ZIP
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size550.2 KiB

Plus4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70406
Missing (%)100.0%
Memory size550.2 KiB

Station Phone
Categorical

HIGH CARDINALITY  IMBALANCE  MISSING 

Distinct17059
Distinct (%)26.2%
Missing5202
Missing (%)7.4%
Memory size550.2 KiB
888-758-4389
29547 
800-663-5633
 
2159
855-999-8378
 
1981
888-356-8911
 
1952
877-798-3752
 
1610
Other values (17054)
27955 

Length

Max length40
Median length12
Mean length13.145758
Min length1

Characters and Unicode

Total characters857156
Distinct characters36
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15334 ?
Unique (%)23.5%

Sample

1st row770-350-3000
2nd row479-783-3188
3rd row866-809-4869
4th row866-809-4869
5th row866-809-4869

Common Values

ValueCountFrequency (%)
888-758-4389 29547
42.0%
800-663-5633 2159
 
3.1%
855-999-8378 1981
 
2.8%
888-356-8911 1952
 
2.8%
877-798-3752 1610
 
2.3%
888-998-2546 1515
 
2.2%
888-264-2208 1118
 
1.6%
855-900-7584 1095
 
1.6%
877-455-3833 899
 
1.3%
833-632-2778 813
 
1.2%
Other values (17049) 22515
32.0%
(Missing) 5202
 
7.4%

Length

2023-08-29T04:25:52.083801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
888-758-4389 29550
41.8%
877-798-3752 7119
 
10.1%
800-663-5633 2159
 
3.1%
855-999-8378 1981
 
2.8%
888-356-8911 1952
 
2.8%
888-998-2546 1517
 
2.1%
888-264-2208 1168
 
1.7%
855-900-7584 1112
 
1.6%
877-455-3833 899
 
1.3%
833-632-2778 814
 
1.2%
Other values (17062) 22375
31.7%

Most occurring characters

ValueCountFrequency (%)
8 219597
25.6%
- 140950
16.4%
7 85220
 
9.9%
3 73854
 
8.6%
5 73730
 
8.6%
9 64936
 
7.6%
4 56544
 
6.6%
2 36993
 
4.3%
0 35937
 
4.2%
6 34391
 
4.0%
Other values (26) 35004
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 705326
82.3%
Dash Punctuation 140950
 
16.4%
Space Separator 10736
 
1.3%
Lowercase Letter 98
 
< 0.1%
Close Punctuation 18
 
< 0.1%
Open Punctuation 13
 
< 0.1%
Other Punctuation 10
 
< 0.1%
Math Symbol 3
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
x 79
80.6%
l 3
 
3.1%
o 3
 
3.1%
a 2
 
2.0%
e 2
 
2.0%
ë 1
 
1.0%
b 1
 
1.0%
r 1
 
1.0%
w 1
 
1.0%
n 1
 
1.0%
Other values (4) 4
 
4.1%
Decimal Number
ValueCountFrequency (%)
8 219597
31.1%
7 85220
 
12.1%
3 73854
 
10.5%
5 73730
 
10.5%
9 64936
 
9.2%
4 56544
 
8.0%
2 36993
 
5.2%
0 35937
 
5.1%
6 34391
 
4.9%
1 24124
 
3.4%
Space Separator
ValueCountFrequency (%)
10735
> 99.9%
  1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 12
92.3%
1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 9
90.0%
/ 1
 
10.0%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
= 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
Ä 1
50.0%
J 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 140950
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 857056
> 99.9%
Latin 100
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
8 219597
25.6%
- 140950
16.4%
7 85220
 
9.9%
3 73854
 
8.6%
5 73730
 
8.6%
9 64936
 
7.6%
4 56544
 
6.6%
2 36993
 
4.3%
0 35937
 
4.2%
6 34391
 
4.0%
Other values (10) 34904
 
4.1%
Latin
ValueCountFrequency (%)
x 79
79.0%
l 3
 
3.0%
o 3
 
3.0%
a 2
 
2.0%
e 2
 
2.0%
ë 1
 
1.0%
b 1
 
1.0%
Ä 1
 
1.0%
r 1
 
1.0%
w 1
 
1.0%
Other values (6) 6
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 857152
> 99.9%
None 3
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 219597
25.6%
- 140950
16.4%
7 85220
 
9.9%
3 73854
 
8.6%
5 73730
 
8.6%
9 64936
 
7.6%
4 56544
 
6.6%
2 36993
 
4.3%
0 35937
 
4.2%
6 34391
 
4.0%
Other values (22) 35000
 
4.1%
None
ValueCountFrequency (%)
ë 1
33.3%
Ä 1
33.3%
  1
33.3%
Punctuation
ValueCountFrequency (%)
1
100.0%

Status Code
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
E
69188 
P
 
986
T
 
232

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters70406
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowE
2nd rowE
3rd rowE
4th rowE
5th rowE

Common Values

ValueCountFrequency (%)
E 69188
98.3%
P 986
 
1.4%
T 232
 
0.3%

Length

2023-08-29T04:25:52.715012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:25:53.090777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
e 69188
98.3%
p 986
 
1.4%
t 232
 
0.3%

Most occurring characters

ValueCountFrequency (%)
E 69188
98.3%
P 986
 
1.4%
T 232
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 70406
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 69188
98.3%
P 986
 
1.4%
T 232
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 70406
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 69188
98.3%
P 986
 
1.4%
T 232
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70406
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 69188
98.3%
P 986
 
1.4%
T 232
 
0.3%

Expected Date
Categorical

HIGH CARDINALITY  MISSING 

Distinct145
Distinct (%)11.9%
Missing69188
Missing (%)98.3%
Memory size550.2 KiB
2022-09-15
576 
2022-09-01
118 
2022-06-15
112 
2022-06-01
 
40
2022-03-15
 
28
Other values (140)
344 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters12180
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)7.4%

Sample

1st row2022-07-15
2nd row2022-05-15
3rd row2022-04-15
4th row2022-05-15
5th row2022-07-01

Common Values

ValueCountFrequency (%)
2022-09-15 576
 
0.8%
2022-09-01 118
 
0.2%
2022-06-15 112
 
0.2%
2022-06-01 40
 
0.1%
2022-03-15 28
 
< 0.1%
2022-10-15 24
 
< 0.1%
2020-09-01 18
 
< 0.1%
2022-08-01 15
 
< 0.1%
2022-11-01 14
 
< 0.1%
2022-10-01 13
 
< 0.1%
Other values (135) 260
 
0.4%
(Missing) 69188
98.3%

Length

2023-08-29T04:25:53.524848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-09-15 576
47.3%
2022-09-01 118
 
9.7%
2022-06-15 112
 
9.2%
2022-06-01 40
 
3.3%
2022-03-15 28
 
2.3%
2022-10-15 24
 
2.0%
2020-09-01 18
 
1.5%
2022-08-01 15
 
1.2%
2022-11-01 14
 
1.1%
2022-10-01 13
 
1.1%
Other values (135) 260
21.3%

Most occurring characters

ValueCountFrequency (%)
2 3609
29.6%
0 2726
22.4%
- 2436
20.0%
1 1397
 
11.5%
5 825
 
6.8%
9 739
 
6.1%
6 193
 
1.6%
3 139
 
1.1%
7 48
 
0.4%
8 38
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9744
80.0%
Dash Punctuation 2436
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3609
37.0%
0 2726
28.0%
1 1397
 
14.3%
5 825
 
8.5%
9 739
 
7.6%
6 193
 
2.0%
3 139
 
1.4%
7 48
 
0.5%
8 38
 
0.4%
4 30
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 2436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3609
29.6%
0 2726
22.4%
- 2436
20.0%
1 1397
 
11.5%
5 825
 
6.8%
9 739
 
6.1%
6 193
 
1.6%
3 139
 
1.1%
7 48
 
0.4%
8 38
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3609
29.6%
0 2726
22.4%
- 2436
20.0%
1 1397
 
11.5%
5 825
 
6.8%
9 739
 
6.1%
6 193
 
1.6%
3 139
 
1.1%
7 48
 
0.4%
8 38
 
0.3%
Distinct28
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
Public
58045 
Private
 
3849
Public - Credit card at all times
 
3629
Public - Call ahead
 
1776
Private - Government only
 
939
Other values (23)
 
2168

Length

Max length64
Median length6
Mean length8.9340113
Min length6

Characters and Unicode

Total characters629008
Distinct characters41
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowPrivate
2nd rowPublic - Card key at all times
3rd rowPrivate - Government only
4th rowPrivate
5th rowPublic - Credit card at all times

Common Values

ValueCountFrequency (%)
Public 58045
82.4%
Private 3849
 
5.5%
Public - Credit card at all times 3629
 
5.2%
Public - Call ahead 1776
 
2.5%
Private - Government only 939
 
1.3%
PLANNED - not yet accessible (Public) 795
 
1.1%
Public - Credit card after hours 539
 
0.8%
Public - Card key at all times 214
 
0.3%
TEMPORARILY UNAVAILABLE (Public) 144
 
0.2%
PLANNED - not yet accessible (Private) 130
 
0.2%
Other values (18) 346
 
0.5%

Length

2023-08-29T04:25:54.065327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
public 65325
58.7%
8409
 
7.6%
private 5081
 
4.6%
card 4595
 
4.1%
credit 4308
 
3.9%
at 3990
 
3.6%
all 3990
 
3.6%
times 3990
 
3.6%
call 1800
 
1.6%
ahead 1800
 
1.6%
Other values (15) 8040
 
7.2%

Most occurring characters

ValueCountFrequency (%)
i 79698
12.7%
l 78996
12.6%
c 71685
11.4%
P 71624
11.4%
b 66311
10.5%
u 66013
10.5%
40922
6.5%
a 24648
 
3.9%
e 21162
 
3.4%
t 21054
 
3.3%
Other values (31) 86895
13.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 487406
77.5%
Uppercase Letter 89835
 
14.3%
Space Separator 40922
 
6.5%
Dash Punctuation 8409
 
1.3%
Open Punctuation 1218
 
0.2%
Close Punctuation 1218
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 79698
16.4%
l 78996
16.2%
c 71685
14.7%
b 66311
13.6%
u 66013
13.5%
a 24648
 
5.1%
e 21162
 
4.3%
t 21054
 
4.3%
r 16221
 
3.3%
d 10707
 
2.2%
Other values (9) 30911
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
P 71624
79.7%
C 6395
 
7.1%
N 2204
 
2.5%
A 1914
 
2.1%
L 1685
 
1.9%
E 1450
 
1.6%
D 986
 
1.1%
G 944
 
1.1%
R 465
 
0.5%
I 464
 
0.5%
Other values (8) 1704
 
1.9%
Space Separator
ValueCountFrequency (%)
40922
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8409
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 577241
91.8%
Common 51767
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 79698
13.8%
l 78996
13.7%
c 71685
12.4%
P 71624
12.4%
b 66311
11.5%
u 66013
11.4%
a 24648
 
4.3%
e 21162
 
3.7%
t 21054
 
3.6%
r 16221
 
2.8%
Other values (27) 59829
10.4%
Common
ValueCountFrequency (%)
40922
79.1%
- 8409
 
16.2%
( 1218
 
2.4%
) 1218
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 629008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 79698
12.7%
l 78996
12.6%
c 71685
11.4%
P 71624
11.4%
b 66311
10.5%
u 66013
10.5%
40922
6.5%
a 24648
 
3.9%
e 21162
 
3.4%
t 21054
 
3.3%
Other values (31) 86895
13.8%

Access Days Time
Categorical

HIGH CARDINALITY  IMBALANCE  MISSING 

Distinct2552
Distinct (%)3.8%
Missing3778
Missing (%)5.4%
Memory size550.2 KiB
24 hours daily
45817 
24 hours daily; for customer use only; see front desk for access
 
2276
MO: Not Specified; TU: Not Specified; WE: Not Specified; TH: Not Specified; FR: Not Specified; SA: Not Specified; SU: Not Specified
 
1698
MON: 24 hours | TUE: 24 hours | WED: 24 hours | THU: 24 hours | FRI: 24 hours | SAT: 24 hours | SUN: 24 hours
 
1499
24 hours daily; for Tesla use only
 
1280
Other values (2547)
14058 

Length

Max length270
Median length14
Mean length28.054362
Min length8

Characters and Unicode

Total characters1869206
Distinct characters80
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1838 ?
Unique (%)2.8%

Sample

1st row24 hours daily
2nd row24 hours daily
3rd row24 hours daily; call 866-809-4869 for Clean Energy card
4th row24 hours daily; call 866-809-4869 for Clean Energy card
5th row24 hours daily; call 866-809-4869 for Clean Energy card

Common Values

ValueCountFrequency (%)
24 hours daily 45817
65.1%
24 hours daily; for customer use only; see front desk for access 2276
 
3.2%
MO: Not Specified; TU: Not Specified; WE: Not Specified; TH: Not Specified; FR: Not Specified; SA: Not Specified; SU: Not Specified 1698
 
2.4%
MON: 24 hours | TUE: 24 hours | WED: 24 hours | THU: 24 hours | FRI: 24 hours | SAT: 24 hours | SUN: 24 hours 1499
 
2.1%
24 hours daily; for Tesla use only 1280
 
1.8%
Dealership business hours 1195
 
1.7%
24 hours daily; for customer use only 1082
 
1.5%
6am-12am daily 821
 
1.2%
7am-7pm M-Th and Sat, 7am-8pm F, 9am-5pm Sun 510
 
0.7%
24 hours daily; for customer use only; see valet for access 451
 
0.6%
Other values (2542) 9999
 
14.2%
(Missing) 3778
 
5.4%

Length

2023-08-29T04:25:54.632975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
hours 66109
18.5%
24 64287
18.0%
daily 56329
15.8%
16570
 
4.6%
not 11905
 
3.3%
specified 11898
 
3.3%
for 10096
 
2.8%
only 7137
 
2.0%
use 6942
 
1.9%
customer 3993
 
1.1%
Other values (1561) 101709
28.5%

Most occurring characters

ValueCountFrequency (%)
290349
 
15.5%
o 108985
 
5.8%
s 104295
 
5.6%
a 99043
 
5.3%
r 91700
 
4.9%
i 89969
 
4.8%
u 85855
 
4.6%
2 75204
 
4.0%
d 75144
 
4.0%
l 73273
 
3.9%
Other values (70) 775389
41.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1124225
60.1%
Space Separator 290349
 
15.5%
Decimal Number 229736
 
12.3%
Uppercase Letter 111871
 
6.0%
Other Punctuation 82104
 
4.4%
Dash Punctuation 21466
 
1.1%
Math Symbol 9076
 
0.5%
Open Punctuation 187
 
< 0.1%
Close Punctuation 187
 
< 0.1%
Currency Symbol 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 108985
9.7%
s 104295
9.3%
a 99043
 
8.8%
r 91700
 
8.2%
i 89969
 
8.0%
u 85855
 
7.6%
d 75144
 
6.7%
l 73273
 
6.5%
h 71246
 
6.3%
e 69175
 
6.2%
Other values (17) 255540
22.7%
Uppercase Letter
ValueCountFrequency (%)
S 24520
21.9%
N 15018
13.4%
T 13113
11.7%
U 8919
 
8.0%
F 7466
 
6.7%
M 7090
 
6.3%
E 6166
 
5.5%
A 5140
 
4.6%
W 4833
 
4.3%
O 3827
 
3.4%
Other values (16) 15779
14.1%
Decimal Number
ValueCountFrequency (%)
2 75204
32.7%
4 66083
28.8%
0 46758
20.4%
1 16496
 
7.2%
7 6962
 
3.0%
6 5357
 
2.3%
8 4381
 
1.9%
5 3914
 
1.7%
9 2562
 
1.1%
3 2019
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 47860
58.3%
; 31421
38.3%
, 2588
 
3.2%
& 86
 
0.1%
' 62
 
0.1%
/ 43
 
0.1%
. 20
 
< 0.1%
! 13
 
< 0.1%
@ 9
 
< 0.1%
" 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
| 9063
99.9%
+ 13
 
0.1%
Space Separator
ValueCountFrequency (%)
290349
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21466
100.0%
Open Punctuation
ValueCountFrequency (%)
( 187
100.0%
Close Punctuation
ValueCountFrequency (%)
) 187
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1236096
66.1%
Common 633110
33.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 108985
 
8.8%
s 104295
 
8.4%
a 99043
 
8.0%
r 91700
 
7.4%
i 89969
 
7.3%
u 85855
 
6.9%
d 75144
 
6.1%
l 73273
 
5.9%
h 71246
 
5.8%
e 69175
 
5.6%
Other values (43) 367411
29.7%
Common
ValueCountFrequency (%)
290349
45.9%
2 75204
 
11.9%
4 66083
 
10.4%
: 47860
 
7.6%
0 46758
 
7.4%
; 31421
 
5.0%
- 21466
 
3.4%
1 16496
 
2.6%
| 9063
 
1.4%
7 6962
 
1.1%
Other values (17) 21448
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1869205
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
290349
 
15.5%
o 108985
 
5.8%
s 104295
 
5.6%
a 99043
 
5.3%
r 91700
 
4.9%
i 89969
 
4.8%
u 85855
 
4.6%
2 75204
 
4.0%
d 75144
 
4.0%
l 73273
 
3.9%
Other values (69) 775388
41.5%
None
ValueCountFrequency (%)
é 1
100.0%

Cards Accepted
Categorical

HIGH CARDINALITY  MISSING 

Distinct728
Distinct (%)6.4%
Missing59117
Missing (%)84.0%
Memory size550.2 KiB
A D Debit M V
2317 
A Cash D Debit M V
1268 
A Cash D M V
940 
A Cash D M V Voyager Wright_Exp
838 
A D M V
572 
Other values (723)
5354 

Length

Max length168
Median length112
Mean length25.649305
Min length1

Characters and Unicode

Total characters289555
Distinct characters45
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique418 ?
Unique (%)3.7%

Sample

1st rowComdata FleetOne FuelMan Voyager Wright_Exp
2nd rowFuelMan M V Wright_Exp
3rd rowA CleanEnergy Comdata D FuelMan M V Voyager Wright_Exp
4th rowCleanEnergy D FleetOne FuelMan M V Voyager Wright_Exp
5th rowCleanEnergy D FuelMan M V Voyager Wright_Exp

Common Values

ValueCountFrequency (%)
A D Debit M V 2317
 
3.3%
A Cash D Debit M V 1268
 
1.8%
A Cash D M V 940
 
1.3%
A Cash D M V Voyager Wright_Exp 838
 
1.2%
A D M V 572
 
0.8%
A Cash Checks D M V Voyager Wright_Exp 419
 
0.6%
A Cash D FuelMan M V Voyager Wright_Exp 264
 
0.4%
A Cash Checks D M V 231
 
0.3%
A Cash D Debit M V Voyager Wright_Exp 229
 
0.3%
A ANDROID_PAY APPLE_PAY Cash Checks CREDIT D M V Voyager Wright_Exp 166
 
0.2%
Other values (718) 4045
 
5.7%
(Missing) 59117
84.0%

Length

2023-08-29T04:25:55.150846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
m 10814
15.1%
v 10803
15.1%
a 10092
14.1%
d 9979
13.9%
cash 6572
9.2%
debit 5177
7.2%
wright_exp 3870
 
5.4%
voyager 3556
 
5.0%
checks 1707
 
2.4%
fuelman 1372
 
1.9%
Other values (20) 7764
10.8%

Most occurring characters

ValueCountFrequency (%)
60417
20.9%
D 16862
 
5.8%
e 16277
 
5.6%
V 14359
 
5.0%
a 14183
 
4.9%
h 12752
 
4.4%
A 12589
 
4.3%
M 12186
 
4.2%
C 11922
 
4.1%
t 11343
 
3.9%
Other values (35) 106665
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 128132
44.3%
Uppercase Letter 96132
33.2%
Space Separator 60417
20.9%
Connector Punctuation 4874
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 16277
12.7%
a 14183
11.1%
h 12752
10.0%
t 11343
8.9%
i 10112
 
7.9%
r 9923
 
7.7%
s 8572
 
6.7%
g 7698
 
6.0%
o 5662
 
4.4%
b 5177
 
4.0%
Other values (12) 26433
20.6%
Uppercase Letter
ValueCountFrequency (%)
D 16862
17.5%
V 14359
14.9%
A 12589
13.1%
M 12186
12.7%
C 11922
12.4%
E 6310
 
6.6%
W 3870
 
4.0%
F 3101
 
3.2%
P 3054
 
3.2%
T 2335
 
2.4%
Other values (11) 9544
9.9%
Space Separator
ValueCountFrequency (%)
60417
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4874
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 224264
77.5%
Common 65291
 
22.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 16862
 
7.5%
e 16277
 
7.3%
V 14359
 
6.4%
a 14183
 
6.3%
h 12752
 
5.7%
A 12589
 
5.6%
M 12186
 
5.4%
C 11922
 
5.3%
t 11343
 
5.1%
i 10112
 
4.5%
Other values (33) 91679
40.9%
Common
ValueCountFrequency (%)
60417
92.5%
_ 4874
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 289555
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
60417
20.9%
D 16862
 
5.8%
e 16277
 
5.6%
V 14359
 
5.0%
a 14183
 
4.9%
h 12752
 
4.4%
A 12589
 
4.3%
M 12186
 
4.2%
C 11922
 
4.1%
t 11343
 
3.9%
Other values (35) 106665
36.8%

BD Blends
Categorical

IMBALANCE  MISSING 

Distinct33
Distinct (%)2.7%
Missing69189
Missing (%)98.3%
Memory size550.2 KiB
B20 in summer, B5 in winter
637 
B20
490 
B20, B5
 
33
B99
 
10
B99, B20
 
5
Other values (28)
 
42

Length

Max length36
Median length27
Mean length16.211997
Min length3

Characters and Unicode

Total characters19730
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)1.6%

Sample

1st rowB99, B20
2nd rowB99
3rd rowB20
4th rowB20
5th rowB20

Common Values

ValueCountFrequency (%)
B20 in summer, B5 in winter 637
 
0.9%
B20 490
 
0.7%
B20, B5 33
 
< 0.1%
B99 10
 
< 0.1%
B99, B20 5
 
< 0.1%
B20 in summer 4
 
< 0.1%
B100 4
 
< 0.1%
B99, B20, B5 3
 
< 0.1%
B20 in summer, B10 in winter 3
 
< 0.1%
B100, B50, B20 2
 
< 0.1%
Other values (23) 26
 
< 0.1%
(Missing) 69189
98.3%

Length

2023-08-29T04:25:55.691660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
in 1306
28.6%
b20 1192
26.1%
b5 679
14.9%
summer 655
14.3%
winter 651
14.3%
b99 25
 
0.5%
b100 11
 
0.2%
b50 6
 
0.1%
b10 5
 
0.1%
the 5
 
0.1%
Other values (17) 31
 
0.7%

Most occurring characters

ValueCountFrequency (%)
3349
17.0%
n 1967
10.0%
i 1959
9.9%
B 1932
9.8%
e 1317
 
6.7%
m 1311
 
6.6%
r 1306
 
6.6%
0 1233
 
6.2%
2 1193
 
6.0%
, 712
 
3.6%
Other values (22) 3451
17.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10538
53.4%
Space Separator 3349
 
17.0%
Decimal Number 3195
 
16.2%
Uppercase Letter 1933
 
9.8%
Other Punctuation 712
 
3.6%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1967
18.7%
i 1959
18.6%
e 1317
12.5%
m 1311
12.4%
r 1306
12.4%
t 660
 
6.3%
u 659
 
6.3%
s 657
 
6.2%
w 651
 
6.2%
a 11
 
0.1%
Other values (9) 40
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 1233
38.6%
2 1193
37.3%
5 687
21.5%
9 54
 
1.7%
1 23
 
0.7%
3 3
 
0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
B 1932
99.9%
D 1
 
0.1%
Space Separator
ValueCountFrequency (%)
3349
100.0%
Other Punctuation
ValueCountFrequency (%)
, 712
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12471
63.2%
Common 7259
36.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1967
15.8%
i 1959
15.7%
B 1932
15.5%
e 1317
10.6%
m 1311
10.5%
r 1306
10.5%
t 660
 
5.3%
u 659
 
5.3%
s 657
 
5.3%
w 651
 
5.2%
Other values (11) 52
 
0.4%
Common
ValueCountFrequency (%)
3349
46.1%
0 1233
 
17.0%
2 1193
 
16.4%
, 712
 
9.8%
5 687
 
9.5%
9 54
 
0.7%
1 23
 
0.3%
3 3
 
< 0.1%
- 3
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3349
17.0%
n 1967
10.0%
i 1959
9.9%
B 1932
9.8%
e 1317
 
6.7%
m 1311
 
6.6%
r 1306
 
6.6%
0 1233
 
6.2%
2 1193
 
6.0%
, 712
 
3.6%
Other values (22) 3451
17.5%
Distinct3
Distinct (%)0.2%
Missing68803
Missing (%)97.7%
Memory size550.2 KiB
Q
1155 
T
248 
B
200 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1603
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB
2nd rowQ
3rd rowQ
4th rowB
5th rowQ

Common Values

ValueCountFrequency (%)
Q 1155
 
1.6%
T 248
 
0.4%
B 200
 
0.3%
(Missing) 68803
97.7%

Length

2023-08-29T04:25:56.278121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:25:56.899162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
q 1155
72.1%
t 248
 
15.5%
b 200
 
12.5%

Most occurring characters

ValueCountFrequency (%)
Q 1155
72.1%
T 248
 
15.5%
B 200
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1603
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Q 1155
72.1%
T 248
 
15.5%
B 200
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1603
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Q 1155
72.1%
T 248
 
15.5%
B 200
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1603
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Q 1155
72.1%
T 248
 
15.5%
B 200
 
12.5%

NG PSI
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68809
Missing (%)97.7%
Memory size550.2 KiB

EV Level1 EVSE Num
Real number (ℝ)

Distinct24
Distinct (%)8.4%
Missing70120
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean3.4615385
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size550.2 KiB
2023-08-29T04:25:57.276253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile15.75
Maximum51
Range50
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.5483564
Coefficient of variation (CV)1.8917474
Kurtosis23.942811
Mean3.4615385
Median Absolute Deviation (MAD)0
Skewness4.5093484
Sum990
Variance42.880972
MonotonicityNot monotonic
2023-08-29T04:25:57.658320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 166
 
0.2%
2 56
 
0.1%
4 16
 
< 0.1%
10 7
 
< 0.1%
3 6
 
< 0.1%
6 6
 
< 0.1%
5 6
 
< 0.1%
18 3
 
< 0.1%
15 3
 
< 0.1%
22 2
 
< 0.1%
Other values (14) 15
 
< 0.1%
(Missing) 70120
99.6%
ValueCountFrequency (%)
1 166
0.2%
2 56
 
0.1%
3 6
 
< 0.1%
4 16
 
< 0.1%
5 6
 
< 0.1%
6 6
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
10 7
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
51 1
 
< 0.1%
47 1
 
< 0.1%
42 1
 
< 0.1%
40 1
 
< 0.1%
28 1
 
< 0.1%
23 1
 
< 0.1%
22 2
< 0.1%
20 1
 
< 0.1%
19 1
 
< 0.1%
18 3
< 0.1%

EV Level2 EVSE Num
Real number (ℝ)

MISSING  SKEWED 

Distinct63
Distinct (%)0.1%
Missing16262
Missing (%)23.1%
Infinite0
Infinite (%)0.0%
Mean2.3152889
Minimum1
Maximum311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size550.2 KiB
2023-08-29T04:25:58.172044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile4
Maximum311
Range310
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1573873
Coefficient of variation (CV)1.3637121
Kurtosis2042.5102
Mean2.3152889
Median Absolute Deviation (MAD)0
Skewness29.922382
Sum125359
Variance9.9690949
MonotonicityNot monotonic
2023-08-29T04:25:58.559065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 33310
47.3%
1 13105
 
18.6%
4 2978
 
4.2%
3 2053
 
2.9%
6 813
 
1.2%
8 387
 
0.5%
5 365
 
0.5%
10 327
 
0.5%
12 133
 
0.2%
7 118
 
0.2%
Other values (53) 555
 
0.8%
(Missing) 16262
23.1%
ValueCountFrequency (%)
1 13105
 
18.6%
2 33310
47.3%
3 2053
 
2.9%
4 2978
 
4.2%
5 365
 
0.5%
6 813
 
1.2%
7 118
 
0.2%
8 387
 
0.5%
9 93
 
0.1%
10 327
 
0.5%
ValueCountFrequency (%)
311 1
< 0.1%
156 1
< 0.1%
128 1
< 0.1%
123 1
< 0.1%
108 1
< 0.1%
106 1
< 0.1%
100 2
< 0.1%
91 1
< 0.1%
81 1
< 0.1%
73 1
< 0.1%

EV DC Fast Count
Real number (ℝ)

Distinct32
Distinct (%)0.4%
Missing62099
Missing (%)88.2%
Infinite0
Infinite (%)0.0%
Mean3.5763814
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size550.2 KiB
2023-08-29T04:25:58.944904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile12
Maximum56
Range55
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.1294705
Coefficient of variation (CV)1.1546505
Kurtosis15.019183
Mean3.5763814
Median Absolute Deviation (MAD)1
Skewness2.8932971
Sum29709
Variance17.052527
MonotonicityNot monotonic
2023-08-29T04:25:59.386944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 3755
 
5.3%
2 1501
 
2.1%
4 889
 
1.3%
8 885
 
1.3%
6 307
 
0.4%
3 262
 
0.4%
12 257
 
0.4%
10 148
 
0.2%
16 89
 
0.1%
20 63
 
0.1%
Other values (22) 151
 
0.2%
(Missing) 62099
88.2%
ValueCountFrequency (%)
1 3755
5.3%
2 1501
 
2.1%
3 262
 
0.4%
4 889
 
1.3%
5 23
 
< 0.1%
6 307
 
0.4%
7 18
 
< 0.1%
8 885
 
1.3%
9 8
 
< 0.1%
10 148
 
0.2%
ValueCountFrequency (%)
56 2
< 0.1%
43 1
 
< 0.1%
40 3
< 0.1%
36 1
 
< 0.1%
35 1
 
< 0.1%
34 1
 
< 0.1%
32 1
 
< 0.1%
30 1
 
< 0.1%
28 4
< 0.1%
26 3
< 0.1%

EV Other Info
Categorical

Distinct9
Distinct (%)18.4%
Missing70357
Missing (%)99.9%
Memory size550.2 KiB
L2
17 
1 SP Inductive
16 
DCFC
1 LP Inductive
3 SP Inductive
 
1
Other values (4)

Length

Max length18
Median length17
Mean length8.4897959
Min length2

Characters and Unicode

Total characters416
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)10.2%

Sample

1st row1 SP Inductive
2nd row1 SP Inductive
3rd row1 SP Inductive
4th row1 SP Inductive
5th row1 SP Inductive

Common Values

ValueCountFrequency (%)
L2 17
 
< 0.1%
1 SP Inductive 16
 
< 0.1%
DCFC 8
 
< 0.1%
1 LP Inductive 3
 
< 0.1%
3 SP Inductive 1
 
< 0.1%
2 Tesla Conductive 1
 
< 0.1%
1 Tesla Conductive 1
 
< 0.1%
1 Conductive 120V 1
 
< 0.1%
7 Conductive 120V 1
 
< 0.1%
(Missing) 70357
99.9%

Length

2023-08-29T04:25:59.819211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:00.193558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 21
21.6%
inductive 20
20.6%
l2 17
17.5%
sp 17
17.5%
dcfc 8
 
8.2%
conductive 4
 
4.1%
lp 3
 
3.1%
tesla 2
 
2.1%
120v 2
 
2.1%
3 1
 
1.0%
Other values (2) 2
 
2.1%

Most occurring characters

ValueCountFrequency (%)
48
 
11.5%
e 26
 
6.2%
v 24
 
5.8%
i 24
 
5.8%
n 24
 
5.8%
d 24
 
5.8%
u 24
 
5.8%
c 24
 
5.8%
t 24
 
5.8%
1 23
 
5.5%
Other values (17) 151
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 204
49.0%
Uppercase Letter 117
28.1%
Space Separator 48
 
11.5%
Decimal Number 47
 
11.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26
12.7%
v 24
11.8%
i 24
11.8%
n 24
11.8%
d 24
11.8%
u 24
11.8%
c 24
11.8%
t 24
11.8%
o 4
 
2.0%
s 2
 
1.0%
Other values (2) 4
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
C 20
17.1%
L 20
17.1%
I 20
17.1%
P 20
17.1%
S 17
14.5%
D 8
 
6.8%
F 8
 
6.8%
T 2
 
1.7%
V 2
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 23
48.9%
2 20
42.6%
0 2
 
4.3%
3 1
 
2.1%
7 1
 
2.1%
Space Separator
ValueCountFrequency (%)
48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 321
77.2%
Common 95
 
22.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26
 
8.1%
v 24
 
7.5%
i 24
 
7.5%
n 24
 
7.5%
d 24
 
7.5%
u 24
 
7.5%
c 24
 
7.5%
t 24
 
7.5%
C 20
 
6.2%
L 20
 
6.2%
Other values (11) 87
27.1%
Common
ValueCountFrequency (%)
48
50.5%
1 23
24.2%
2 20
21.1%
0 2
 
2.1%
3 1
 
1.1%
7 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
 
11.5%
e 26
 
6.2%
v 24
 
5.8%
i 24
 
5.8%
n 24
 
5.8%
d 24
 
5.8%
u 24
 
5.8%
c 24
 
5.8%
t 24
 
5.8%
1 23
 
5.5%
Other values (17) 151
36.3%

EV Network
Categorical

Distinct34
Distinct (%)0.1%
Missing9499
Missing (%)13.5%
Memory size550.2 KiB
ChargePoint Network
29680 
Non-Networked
10602 
Tesla Destination
4906 
SemaCharge Network
 
2178
Circuit électrique
 
1986
Other values (29)
11555 

Length

Max length23
Median length19
Mean length15.697194
Min length3

Characters and Unicode

Total characters956069
Distinct characters50
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon-Networked
2nd rowNon-Networked
3rd rowNon-Networked
4th rowNon-Networked
5th rowNon-Networked

Common Values

ValueCountFrequency (%)
ChargePoint Network 29680
42.2%
Non-Networked 10602
 
15.1%
Tesla Destination 4906
 
7.0%
SemaCharge Network 2178
 
3.1%
Circuit électrique 1986
 
2.8%
FLO 1956
 
2.8%
Tesla 1575
 
2.2%
Blink Network 1511
 
2.1%
Volta 1240
 
1.8%
Greenlots 1115
 
1.6%
Other values (24) 4158
 
5.9%
(Missing) 9499
 
13.5%

Length

2023-08-29T04:26:00.639920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
network 34361
33.0%
chargepoint 29680
28.5%
non-networked 10602
 
10.2%
tesla 6481
 
6.2%
destination 4906
 
4.7%
semacharge 2178
 
2.1%
circuit 1986
 
1.9%
électrique 1986
 
1.9%
flo 1956
 
1.9%
blink 1511
 
1.5%
Other values (31) 8345
 
8.0%

Most occurring characters

ValueCountFrequency (%)
e 111132
11.6%
o 94630
 
9.9%
t 92834
 
9.7%
r 83651
 
8.7%
N 56257
 
5.9%
n 55047
 
5.8%
i 48627
 
5.1%
a 47713
 
5.0%
k 46474
 
4.9%
w 44966
 
4.7%
Other values (40) 274738
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 745894
78.0%
Uppercase Letter 156424
 
16.4%
Space Separator 43085
 
4.5%
Dash Punctuation 10602
 
1.1%
Connector Punctuation 64
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 56257
36.0%
C 35646
22.8%
P 30029
19.2%
T 6999
 
4.5%
D 5007
 
3.2%
V 3591
 
2.3%
S 2640
 
1.7%
O 2630
 
1.7%
E 2405
 
1.5%
L 2358
 
1.5%
Other values (14) 8862
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
e 111132
14.9%
o 94630
12.7%
t 92834
12.4%
r 83651
11.2%
n 55047
7.4%
i 48627
6.5%
a 47713
6.4%
k 46474
6.2%
w 44966
6.0%
g 32857
 
4.4%
Other values (13) 87963
11.8%
Space Separator
ValueCountFrequency (%)
43085
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10602
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 902318
94.4%
Common 53751
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 111132
12.3%
o 94630
10.5%
t 92834
10.3%
r 83651
 
9.3%
N 56257
 
6.2%
n 55047
 
6.1%
i 48627
 
5.4%
a 47713
 
5.3%
k 46474
 
5.2%
w 44966
 
5.0%
Other values (37) 220987
24.5%
Common
ValueCountFrequency (%)
43085
80.2%
- 10602
 
19.7%
_ 64
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 954081
99.8%
None 1988
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 111132
11.6%
o 94630
 
9.9%
t 92834
 
9.7%
r 83651
 
8.8%
N 56257
 
5.9%
n 55047
 
5.8%
i 48627
 
5.1%
a 47713
 
5.0%
k 46474
 
4.9%
w 44966
 
4.7%
Other values (38) 272750
28.6%
None
ValueCountFrequency (%)
é 1986
99.9%
É 2
 
0.1%

EV Network Web
Categorical

IMBALANCE  MISSING 

Distinct32
Distinct (%)0.1%
Missing20101
Missing (%)28.6%
Memory size550.2 KiB
http://www.chargepoint.com/
29680 
https://www.tesla.com/destination-charging
4906 
https://semaconnect.com/
 
2178
https://lecircuitelectrique.com/
 
1986
https://flo.ca/
 
1956
Other values (27)
9599 

Length

Max length86
Median length27
Mean length28.199344
Min length15

Characters and Unicode

Total characters1418568
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://voltacharging.com/
2nd rowhttps://voltacharging.com/
3rd rowhttp://evconnect.com/
4th rowhttp://evconnect.com/
5th rowhttp://evconnect.com/

Common Values

ValueCountFrequency (%)
http://www.chargepoint.com/ 29680
42.2%
https://www.tesla.com/destination-charging 4906
 
7.0%
https://semaconnect.com/ 2178
 
3.1%
https://lecircuitelectrique.com/ 1986
 
2.8%
https://flo.ca/ 1956
 
2.8%
https://www.tesla.com/supercharger 1575
 
2.2%
http://www.blinkcharging.com/ 1511
 
2.1%
https://voltacharging.com/ 1240
 
1.8%
http://greenlots.com/ 1115
 
1.6%
http://evconnect.com/ 979
 
1.4%
Other values (22) 3179
 
4.5%
(Missing) 20101
28.6%

Length

2023-08-29T04:26:01.051181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
http://www.chargepoint.com 29680
59.0%
https://www.tesla.com/destination-charging 4906
 
9.8%
https://semaconnect.com 2178
 
4.3%
https://lecircuitelectrique.com 1986
 
3.9%
https://flo.ca 1956
 
3.9%
https://www.tesla.com/supercharger 1575
 
3.1%
http://www.blinkcharging.com 1511
 
3.0%
https://voltacharging.com 1240
 
2.5%
http://greenlots.com 1115
 
2.2%
http://evconnect.com 979
 
1.9%
Other values (22) 3179
 
6.3%

Most occurring characters

ValueCountFrequency (%)
t 158153
 
11.1%
/ 151353
 
10.7%
w 121324
 
8.6%
c 104689
 
7.4%
o 92627
 
6.5%
. 90609
 
6.4%
h 90217
 
6.4%
p 82231
 
5.8%
e 67822
 
4.8%
a 58789
 
4.1%
Other values (19) 400754
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1120764
79.0%
Other Punctuation 292267
 
20.6%
Dash Punctuation 5537
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 158153
14.1%
w 121324
10.8%
c 104689
9.3%
o 92627
8.3%
h 90217
 
8.0%
p 82231
 
7.3%
e 67822
 
6.1%
a 58789
 
5.2%
n 58058
 
5.2%
i 57415
 
5.1%
Other values (15) 229439
20.5%
Other Punctuation
ValueCountFrequency (%)
/ 151353
51.8%
. 90609
31.0%
: 50305
 
17.2%
Dash Punctuation
ValueCountFrequency (%)
- 5537
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1120764
79.0%
Common 297804
 
21.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 158153
14.1%
w 121324
10.8%
c 104689
9.3%
o 92627
8.3%
h 90217
 
8.0%
p 82231
 
7.3%
e 67822
 
6.1%
a 58789
 
5.2%
n 58058
 
5.2%
i 57415
 
5.1%
Other values (15) 229439
20.5%
Common
ValueCountFrequency (%)
/ 151353
50.8%
. 90609
30.4%
: 50305
 
16.9%
- 5537
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1418568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 158153
 
11.1%
/ 151353
 
10.7%
w 121324
 
8.6%
c 104689
 
7.4%
o 92627
 
6.5%
. 90609
 
6.4%
h 90217
 
6.4%
p 82231
 
5.8%
e 67822
 
4.8%
a 58789
 
4.1%
Other values (19) 400754
28.3%

Geocode Status
Categorical

Distinct7
Distinct (%)< 0.1%
Missing15
Missing (%)< 0.1%
Memory size550.2 KiB
GPS
51574 
200-9
14506 
200-8
 
4241
200-6
 
56
200-5
 
11
Other values (2)
 
3

Length

Max length5
Median length3
Mean length3.5346422
Min length3

Characters and Unicode

Total characters248807
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row200-9
2nd row200-8
3rd row200-8
4th row200-9
5th row200-9

Common Values

ValueCountFrequency (%)
GPS 51574
73.3%
200-9 14506
 
20.6%
200-8 4241
 
6.0%
200-6 56
 
0.1%
200-5 11
 
< 0.1%
200-7 2
 
< 0.1%
200-4 1
 
< 0.1%
(Missing) 15
 
< 0.1%

Length

2023-08-29T04:26:01.517934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:01.889745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gps 51574
73.3%
200-9 14506
 
20.6%
200-8 4241
 
6.0%
200-6 56
 
0.1%
200-5 11
 
< 0.1%
200-7 2
 
< 0.1%
200-4 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
G 51574
20.7%
P 51574
20.7%
S 51574
20.7%
0 37634
15.1%
2 18817
 
7.6%
- 18817
 
7.6%
9 14506
 
5.8%
8 4241
 
1.7%
6 56
 
< 0.1%
5 11
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 154722
62.2%
Decimal Number 75268
30.3%
Dash Punctuation 18817
 
7.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37634
50.0%
2 18817
25.0%
9 14506
 
19.3%
8 4241
 
5.6%
6 56
 
0.1%
5 11
 
< 0.1%
7 2
 
< 0.1%
4 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
G 51574
33.3%
P 51574
33.3%
S 51574
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 18817
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 154722
62.2%
Common 94085
37.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37634
40.0%
2 18817
20.0%
- 18817
20.0%
9 14506
 
15.4%
8 4241
 
4.5%
6 56
 
0.1%
5 11
 
< 0.1%
7 2
 
< 0.1%
4 1
 
< 0.1%
Latin
ValueCountFrequency (%)
G 51574
33.3%
P 51574
33.3%
S 51574
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 248807
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
G 51574
20.7%
P 51574
20.7%
S 51574
20.7%
0 37634
15.1%
2 18817
 
7.6%
- 18817
 
7.6%
9 14506
 
5.8%
8 4241
 
1.7%
6 56
 
< 0.1%
5 11
 
< 0.1%
Other values (2) 3
 
< 0.1%

Latitude
Real number (ℝ)

Distinct67078
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.929309
Minimum0
Maximum64.852466
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size550.2 KiB
2023-08-29T04:26:02.456409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile29.616869
Q134.182981
median39.105989
Q342.702185
95-th percentile47.70926
Maximum64.852466
Range64.852466
Interquartile range (IQR)8.5192045

Descriptive statistics

Standard deviation5.6284583
Coefficient of variation (CV)0.14458151
Kurtosis0.23432981
Mean38.929309
Median Absolute Deviation (MAD)4.0084545
Skewness-0.1338145
Sum2740856.9
Variance31.679543
MonotonicityNot monotonic
2023-08-29T04:26:03.081742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46.347582 19
 
< 0.1%
37.6161599 12
 
< 0.1%
46.351004 10
 
< 0.1%
37.875902 10
 
< 0.1%
35.9311 10
 
< 0.1%
39.7959446 8
 
< 0.1%
33.317842 7
 
< 0.1%
38.8702 7
 
< 0.1%
35.6462683 6
 
< 0.1%
37.3688889 6
 
< 0.1%
Other values (67068) 70311
99.9%
ValueCountFrequency (%)
0 1
< 0.1%
18.334138 1
< 0.1%
18.365585 1
< 0.1%
18.369873 1
< 0.1%
18.375312 1
< 0.1%
18.389079 1
< 0.1%
18.412531 1
< 0.1%
18.42107 1
< 0.1%
19.062777 1
< 0.1%
19.20214322 1
< 0.1%
ValueCountFrequency (%)
64.852466 1
< 0.1%
64.0642103 1
< 0.1%
64.055428 1
< 0.1%
63.86892416 1
< 0.1%
63.74598652 1
< 0.1%
63.594806 1
< 0.1%
63.44725602 1
< 0.1%
63.38793423 1
< 0.1%
63.37567 1
< 0.1%
63.0376192 1
< 0.1%

Longitude
Real number (ℝ)

Distinct67388
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-96.061447
Minimum-159.78856
Maximum40.432278
Zeros2
Zeros (%)< 0.1%
Negative70403
Negative (%)> 99.9%
Memory size550.2 KiB
2023-08-29T04:26:03.684963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-159.78856
5-th percentile-122.47753
Q1-117.86056
median-92.002897
Q3-78.881493
95-th percentile-71.372179
Maximum40.432278
Range200.22083
Interquartile range (IQR)38.97907

Descriptive statistics

Standard deviation19.545273
Coefficient of variation (CV)-0.20346636
Kurtosis-1.0629781
Mean-96.061447
Median Absolute Deviation (MAD)17.651217
Skewness-0.33006295
Sum-6763302.3
Variance382.01769
MonotonicityNot monotonic
2023-08-29T04:26:04.243434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-119.277892 19
 
< 0.1%
-122.3968687 12
 
< 0.1%
-84.309978 10
 
< 0.1%
-122.250055 10
 
< 0.1%
-104.9012885 8
 
< 0.1%
-117.320512 7
 
< 0.1%
-117.8130199 7
 
< 0.1%
-86.834112 6
 
< 0.1%
-119.283199 6
 
< 0.1%
-73.955605 6
 
< 0.1%
Other values (67378) 70315
99.9%
ValueCountFrequency (%)
-159.788556 1
< 0.1%
-159.485143 1
< 0.1%
-159.476393 1
< 0.1%
-159.46942 1
< 0.1%
-159.46862 1
< 0.1%
-159.4572297 1
< 0.1%
-159.456719 1
< 0.1%
-159.44208 1
< 0.1%
-159.43897 1
< 0.1%
-159.38643 1
< 0.1%
ValueCountFrequency (%)
40.4322778 1
< 0.1%
0 2
< 0.1%
-43.771088 1
< 0.1%
-52.71009854 1
< 0.1%
-52.710577 1
< 0.1%
-52.7141638 1
< 0.1%
-52.7317803 1
< 0.1%
-52.74192473 1
< 0.1%
-52.75427385 1
< 0.1%
-52.759686 1
< 0.1%

Date Last Confirmed
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct92
Distinct (%)0.1%
Missing218
Missing (%)0.3%
Memory size550.2 KiB
2022-07-25
38756 
2020-11-03
4868 
2022-06-14
 
2185
2022-04-06
 
2171
2022-05-05
 
1847
Other values (87)
20361 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters701880
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st row2022-06-14
2nd row2021-08-04
3rd row2021-08-04
4th row2022-06-14
5th row2022-06-14

Common Values

ValueCountFrequency (%)
2022-07-25 38756
55.0%
2020-11-03 4868
 
6.9%
2022-06-14 2185
 
3.1%
2022-04-06 2171
 
3.1%
2022-05-05 1847
 
2.6%
2022-07-24 1511
 
2.1%
2021-10-11 1278
 
1.8%
2021-10-12 1244
 
1.8%
2021-06-07 1223
 
1.7%
2020-06-09 1201
 
1.7%
Other values (82) 13904
 
19.7%

Length

2023-08-29T04:26:04.647181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-07-25 38756
55.2%
2020-11-03 4868
 
6.9%
2022-06-14 2185
 
3.1%
2022-04-06 2171
 
3.1%
2022-05-05 1847
 
2.6%
2022-07-24 1511
 
2.2%
2021-10-11 1278
 
1.8%
2021-10-12 1244
 
1.8%
2021-06-07 1223
 
1.7%
2020-06-09 1201
 
1.7%
Other values (82) 13904
 
19.8%

Most occurring characters

ValueCountFrequency (%)
2 238287
33.9%
0 161147
23.0%
- 140376
20.0%
7 44521
 
6.3%
5 43581
 
6.2%
1 41550
 
5.9%
4 10709
 
1.5%
3 8460
 
1.2%
6 7524
 
1.1%
9 3699
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 561504
80.0%
Dash Punctuation 140376
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 238287
42.4%
0 161147
28.7%
7 44521
 
7.9%
5 43581
 
7.8%
1 41550
 
7.4%
4 10709
 
1.9%
3 8460
 
1.5%
6 7524
 
1.3%
9 3699
 
0.7%
8 2026
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 140376
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 701880
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 238287
33.9%
0 161147
23.0%
- 140376
20.0%
7 44521
 
6.3%
5 43581
 
6.2%
1 41550
 
5.9%
4 10709
 
1.5%
3 8460
 
1.2%
6 7524
 
1.1%
9 3699
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 701880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 238287
33.9%
0 161147
23.0%
- 140376
20.0%
7 44521
 
6.3%
5 43581
 
6.2%
1 41550
 
5.9%
4 10709
 
1.5%
3 8460
 
1.2%
6 7524
 
1.1%
9 3699
 
0.5%

ID
Real number (ℝ)

Distinct70406
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148730.33
Minimum17
Maximum224382
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size550.2 KiB
2023-08-29T04:26:05.086462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile44494.25
Q1113723.25
median165247.5
Q3190653.75
95-th percentile218030.75
Maximum224382
Range224365
Interquartile range (IQR)76930.5

Descriptive statistics

Standard deviation54261.672
Coefficient of variation (CV)0.3648326
Kurtosis-0.56898951
Mean148730.33
Median Absolute Deviation (MAD)34964
Skewness-0.70719055
Sum1.0471507 × 1010
Variance2.9443291 × 109
MonotonicityStrictly increasing
2023-08-29T04:26:05.510693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17 1
 
< 0.1%
181240 1
 
< 0.1%
181246 1
 
< 0.1%
181245 1
 
< 0.1%
181244 1
 
< 0.1%
181243 1
 
< 0.1%
181242 1
 
< 0.1%
181241 1
 
< 0.1%
181239 1
 
< 0.1%
181266 1
 
< 0.1%
Other values (70396) 70396
> 99.9%
ValueCountFrequency (%)
17 1
< 0.1%
42 1
< 0.1%
45 1
< 0.1%
64 1
< 0.1%
73 1
< 0.1%
81 1
< 0.1%
84 1
< 0.1%
108 1
< 0.1%
112 1
< 0.1%
124 1
< 0.1%
ValueCountFrequency (%)
224382 1
< 0.1%
224381 1
< 0.1%
224380 1
< 0.1%
224377 1
< 0.1%
224376 1
< 0.1%
224375 1
< 0.1%
224374 1
< 0.1%
224373 1
< 0.1%
224371 1
< 0.1%
224369 1
< 0.1%

Updated At
Categorical

Distinct4816
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
2021-03-11 23:22:17 UTC
7202 
2022-02-10 19:42:29 UTC
 
4900
2022-07-25 00:31:01 UTC
 
2141
2022-04-26 16:04:15 UTC
 
2055
2022-07-25 01:50:26 UTC
 
1976
Other values (4811)
52132 

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters1619338
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1279 ?
Unique (%)1.8%

Sample

1st row2022-06-14 16:22:47 UTC
2nd row2022-02-10 19:42:29 UTC
3rd row2022-02-10 19:42:29 UTC
4th row2022-06-14 16:22:47 UTC
5th row2022-06-14 16:22:47 UTC

Common Values

ValueCountFrequency (%)
2021-03-11 23:22:17 UTC 7202
 
10.2%
2022-02-10 19:42:29 UTC 4900
 
7.0%
2022-07-25 00:31:01 UTC 2141
 
3.0%
2022-04-26 16:04:15 UTC 2055
 
2.9%
2022-07-25 01:50:26 UTC 1976
 
2.8%
2022-05-05 20:22:04 UTC 1841
 
2.6%
2022-04-06 14:08:04 UTC 1732
 
2.5%
2022-07-24 22:55:19 UTC 1511
 
2.1%
2022-07-25 01:37:03 UTC 1511
 
2.1%
2021-11-04 18:37:47 UTC 1276
 
1.8%
Other values (4806) 44261
62.9%

Length

2023-08-29T04:26:05.940924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
utc 70406
33.3%
2022-07-25 38760
18.4%
2021-03-11 7202
 
3.4%
23:22:17 7202
 
3.4%
2022-02-10 5017
 
2.4%
19:42:29 4900
 
2.3%
2022-06-14 2223
 
1.1%
00:31:01 2141
 
1.0%
2022-04-26 2055
 
1.0%
16:04:15 2055
 
1.0%
Other values (4917) 69257
32.8%

Most occurring characters

ValueCountFrequency (%)
2 322628
19.9%
0 247447
15.3%
- 140812
8.7%
140812
8.7%
: 140812
8.7%
1 122513
 
7.6%
5 74321
 
4.6%
U 70406
 
4.3%
T 70406
 
4.3%
C 70406
 
4.3%
Other values (6) 218775
13.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 985684
60.9%
Uppercase Letter 211218
 
13.0%
Dash Punctuation 140812
 
8.7%
Space Separator 140812
 
8.7%
Other Punctuation 140812
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 322628
32.7%
0 247447
25.1%
1 122513
 
12.4%
5 74321
 
7.5%
7 64516
 
6.5%
4 50496
 
5.1%
3 45882
 
4.7%
6 23041
 
2.3%
9 21066
 
2.1%
8 13774
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
U 70406
33.3%
T 70406
33.3%
C 70406
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 140812
100.0%
Space Separator
ValueCountFrequency (%)
140812
100.0%
Other Punctuation
ValueCountFrequency (%)
: 140812
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1408120
87.0%
Latin 211218
 
13.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 322628
22.9%
0 247447
17.6%
- 140812
10.0%
140812
10.0%
: 140812
10.0%
1 122513
 
8.7%
5 74321
 
5.3%
7 64516
 
4.6%
4 50496
 
3.6%
3 45882
 
3.3%
Other values (3) 57881
 
4.1%
Latin
ValueCountFrequency (%)
U 70406
33.3%
T 70406
33.3%
C 70406
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1619338
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 322628
19.9%
0 247447
15.3%
- 140812
8.7%
140812
8.7%
: 140812
8.7%
1 122513
 
7.6%
5 74321
 
4.6%
U 70406
 
4.3%
T 70406
 
4.3%
C 70406
 
4.3%
Other values (6) 218775
13.5%

Owner Type Code
Categorical

IMBALANCE  MISSING 

Distinct6
Distinct (%)< 0.1%
Missing40216
Missing (%)57.1%
Memory size550.2 KiB
P
25636 
LG
 
1961
FG
 
958
T
 
931
SG
 
685

Length

Max length2
Median length1
Mean length1.1193773
Min length1

Characters and Unicode

Total characters33794
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowT
2nd rowP
3rd rowLG
4th rowP
5th rowT

Common Values

ValueCountFrequency (%)
P 25636
36.4%
LG 1961
 
2.8%
FG 958
 
1.4%
T 931
 
1.3%
SG 685
 
1.0%
J 19
 
< 0.1%
(Missing) 40216
57.1%

Length

2023-08-29T04:26:06.343478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:06.656041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
p 25636
84.9%
lg 1961
 
6.5%
fg 958
 
3.2%
t 931
 
3.1%
sg 685
 
2.3%
j 19
 
0.1%

Most occurring characters

ValueCountFrequency (%)
P 25636
75.9%
G 3604
 
10.7%
L 1961
 
5.8%
F 958
 
2.8%
T 931
 
2.8%
S 685
 
2.0%
J 19
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 33794
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 25636
75.9%
G 3604
 
10.7%
L 1961
 
5.8%
F 958
 
2.8%
T 931
 
2.8%
S 685
 
2.0%
J 19
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 33794
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 25636
75.9%
G 3604
 
10.7%
L 1961
 
5.8%
F 958
 
2.8%
T 931
 
2.8%
S 685
 
2.0%
J 19
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33794
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 25636
75.9%
G 3604
 
10.7%
L 1961
 
5.8%
F 958
 
2.8%
T 931
 
2.8%
S 685
 
2.0%
J 19
 
0.1%

Federal Agency ID
Real number (ℝ)

Distinct26
Distinct (%)2.7%
Missing69451
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean13.905759
Minimum2
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size550.2 KiB
2023-08-29T04:26:07.010603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q18
median14
Q317
95-th percentile26
Maximum60
Range58
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.7674395
Coefficient of variation (CV)0.48666451
Kurtosis1.3296291
Mean13.905759
Median Absolute Deviation (MAD)5
Skewness0.58978883
Sum13280
Variance45.798237
MonotonicityNot monotonic
2023-08-29T04:26:07.349083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
14 200
 
0.3%
16 134
 
0.2%
8 126
 
0.2%
26 78
 
0.1%
5 69
 
0.1%
6 58
 
0.1%
19 58
 
0.1%
17 27
 
< 0.1%
12 24
 
< 0.1%
22 24
 
< 0.1%
Other values (16) 157
 
0.2%
(Missing) 69451
98.6%
ValueCountFrequency (%)
2 7
 
< 0.1%
3 14
 
< 0.1%
4 22
 
< 0.1%
5 69
0.1%
6 58
0.1%
7 8
 
< 0.1%
8 126
0.2%
9 14
 
< 0.1%
10 20
 
< 0.1%
12 24
 
< 0.1%
ValueCountFrequency (%)
60 1
 
< 0.1%
29 8
 
< 0.1%
26 78
0.1%
25 19
 
< 0.1%
24 8
 
< 0.1%
23 12
 
< 0.1%
22 24
 
< 0.1%
21 5
 
< 0.1%
20 15
 
< 0.1%
19 58
0.1%
Distinct26
Distinct (%)2.7%
Missing69451
Missing (%)98.6%
Memory size550.2 KiB
Department of Navy
200 
Department of the Interior
134 
U.S. Department of Energy
126 
United States Marine Corps
78 
Department of Air Force
69 
Other values (21)
348 

Length

Max length45
Median length39
Mean length24.384293
Min length9

Characters and Unicode

Total characters23287
Distinct characters42
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st rowUnited States Marine Corps
2nd rowDepartment of the Interior
3rd rowDepartment of Air Force
4th rowDepartment of Air Force
5th rowDepartment of Air Force

Common Values

ValueCountFrequency (%)
Department of Navy 200
 
0.3%
Department of the Interior 134
 
0.2%
U.S. Department of Energy 126
 
0.2%
United States Marine Corps 78
 
0.1%
Department of Air Force 69
 
0.1%
Department of Army 58
 
0.1%
Department of Veterans Affairs 58
 
0.1%
Department of Transportation 27
 
< 0.1%
Department of Justice 24
 
< 0.1%
National Aeronautics and Space Administration 24
 
< 0.1%
Other values (16) 157
 
0.2%
(Missing) 69451
98.6%

Length

2023-08-29T04:26:08.101028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
of 779
22.4%
department 772
22.2%
navy 200
 
5.8%
u.s 190
 
5.5%
the 134
 
3.9%
interior 134
 
3.9%
energy 126
 
3.6%
corps 85
 
2.4%
united 78
 
2.2%
states 78
 
2.2%
Other values (38) 895
25.8%

Most occurring characters

ValueCountFrequency (%)
e 2771
11.9%
2516
10.8%
t 2483
 
10.7%
r 1930
 
8.3%
n 1673
 
7.2%
a 1581
 
6.8%
o 1339
 
5.7%
m 944
 
4.1%
f 917
 
3.9%
p 909
 
3.9%
Other values (32) 6224
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17674
75.9%
Uppercase Letter 2710
 
11.6%
Space Separator 2516
 
10.8%
Other Punctuation 387
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2771
15.7%
t 2483
14.0%
r 1930
10.9%
n 1673
9.5%
a 1581
8.9%
o 1339
7.6%
m 944
 
5.3%
f 917
 
5.2%
p 909
 
5.1%
i 836
 
4.7%
Other values (11) 2291
13.0%
Uppercase Letter
ValueCountFrequency (%)
D 794
29.3%
S 379
14.0%
A 297
 
11.0%
U 268
 
9.9%
N 224
 
8.3%
E 148
 
5.5%
I 146
 
5.4%
C 100
 
3.7%
M 78
 
2.9%
F 69
 
2.5%
Other values (8) 207
 
7.6%
Other Punctuation
ValueCountFrequency (%)
. 380
98.2%
, 7
 
1.8%
Space Separator
ValueCountFrequency (%)
2516
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20384
87.5%
Common 2903
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2771
13.6%
t 2483
12.2%
r 1930
 
9.5%
n 1673
 
8.2%
a 1581
 
7.8%
o 1339
 
6.6%
m 944
 
4.6%
f 917
 
4.5%
p 909
 
4.5%
i 836
 
4.1%
Other values (29) 5001
24.5%
Common
ValueCountFrequency (%)
2516
86.7%
. 380
 
13.1%
, 7
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23287
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2771
11.9%
2516
10.8%
t 2483
 
10.7%
r 1930
 
8.3%
n 1673
 
7.2%
a 1581
 
6.8%
o 1339
 
5.7%
m 944
 
4.1%
f 917
 
3.9%
p 909
 
3.9%
Other values (32) 6224
26.7%

Open Date
Categorical

HIGH CARDINALITY  MISSING 

Distinct3796
Distinct (%)5.5%
Missing1096
Missing (%)1.6%
Memory size550.2 KiB
2021-01-27
9704 
2020-06-12
 
3089
2019-07-17
 
1645
2018-11-01
 
1030
2021-10-25
 
777
Other values (3791)
53065 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters693100
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique951 ?
Unique (%)1.4%

Sample

1st row2010-12-01
2nd row1994-07-15
3rd row1996-12-15
4th row1997-01-01
5th row1997-01-01

Common Values

ValueCountFrequency (%)
2021-01-27 9704
 
13.8%
2020-06-12 3089
 
4.4%
2019-07-17 1645
 
2.3%
2018-11-01 1030
 
1.5%
2021-10-25 777
 
1.1%
2012-01-31 714
 
1.0%
2020-11-03 650
 
0.9%
2021-01-15 548
 
0.8%
2017-09-01 536
 
0.8%
2011-03-15 491
 
0.7%
Other values (3786) 50126
71.2%
(Missing) 1096
 
1.6%

Length

2023-08-29T04:26:08.537324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-01-27 9704
 
14.0%
2020-06-12 3089
 
4.5%
2019-07-17 1645
 
2.4%
2018-11-01 1030
 
1.5%
2021-10-25 777
 
1.1%
2012-01-31 714
 
1.0%
2020-11-03 650
 
0.9%
2021-01-15 548
 
0.8%
2017-09-01 536
 
0.8%
2011-03-15 491
 
0.7%
Other values (3786) 50126
72.3%

Most occurring characters

ValueCountFrequency (%)
0 166896
24.1%
2 157526
22.7%
- 138620
20.0%
1 122158
17.6%
7 24351
 
3.5%
5 17762
 
2.6%
9 16305
 
2.4%
3 14314
 
2.1%
6 13830
 
2.0%
8 11551
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 554480
80.0%
Dash Punctuation 138620
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 166896
30.1%
2 157526
28.4%
1 122158
22.0%
7 24351
 
4.4%
5 17762
 
3.2%
9 16305
 
2.9%
3 14314
 
2.6%
6 13830
 
2.5%
8 11551
 
2.1%
4 9787
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 138620
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 693100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 166896
24.1%
2 157526
22.7%
- 138620
20.0%
1 122158
17.6%
7 24351
 
3.5%
5 17762
 
2.6%
9 16305
 
2.4%
3 14314
 
2.1%
6 13830
 
2.0%
8 11551
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 693100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 166896
24.1%
2 157526
22.7%
- 138620
20.0%
1 122158
17.6%
7 24351
 
3.5%
5 17762
 
2.6%
9 16305
 
2.4%
3 14314
 
2.1%
6 13830
 
2.0%
8 11551
 
1.7%

Hydrogen Status Link
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct82
Distinct (%)98.8%
Missing70323
Missing (%)99.9%
Memory size550.2 KiB
https://cafcp.org/stationmap
 
2
http://cafcp.org/content/concord
 
1
http://cafcp.org/content/los-gatos
 
1
http://cafcp.org/content/glendale
 
1
http://cafcp.org/content/buena-park
 
1
Other values (77)
77 

Length

Max length52
Median length46
Mean length37.481928
Min length28

Characters and Unicode

Total characters3111
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)97.6%

Sample

1st rowhttp://m.cafcp.org/content/uc-irvine
2nd rowhttps://m.cafcp.org/content/torrance-0
3rd rowhttp://m.cafcp.org/content/lax
4th rowhttp://m.cafcp.org/content/emeryville-upgrade
5th rowhttps://cafcp.org/stationmap

Common Values

ValueCountFrequency (%)
https://cafcp.org/stationmap 2
 
< 0.1%
http://cafcp.org/content/concord 1
 
< 0.1%
http://cafcp.org/content/los-gatos 1
 
< 0.1%
http://cafcp.org/content/glendale 1
 
< 0.1%
http://cafcp.org/content/buena-park 1
 
< 0.1%
http://cafcp.org/content/el-cerrito 1
 
< 0.1%
http://cafcp.org/content/san-bernardino 1
 
< 0.1%
http://cafcp.org/content/baldwin-park 1
 
< 0.1%
http://cafcp.org/content/aliso-viejo 1
 
< 0.1%
http://cafcp.org/content/plancentia 1
 
< 0.1%
Other values (72) 72
 
0.1%
(Missing) 70323
99.9%

Length

2023-08-29T04:26:08.922439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://cafcp.org/stationmap 2
 
2.4%
http://m.cafcp.org/content/playa-del-rey 1
 
1.2%
http://m.cafcp.org/content/lax 1
 
1.2%
http://m.cafcp.org/content/emeryville-upgrade 1
 
1.2%
http://m.cafcp.org/content/palo-alto 1
 
1.2%
http://m.cafcp.org/content/anaheim 1
 
1.2%
http://m.cafcp.org/content/fairfax-la 1
 
1.2%
http://m.cafcp.org/content/cal-state-la 1
 
1.2%
https://cafcp.org/content/cupertino 1
 
1.2%
http://m.cafcp.org/content/campbell 1
 
1.2%
Other values (72) 72
86.7%

Most occurring characters

ValueCountFrequency (%)
t 376
12.1%
/ 330
 
10.6%
c 283
 
9.1%
n 237
 
7.6%
a 230
 
7.4%
o 228
 
7.3%
p 182
 
5.9%
e 147
 
4.7%
r 143
 
4.6%
. 128
 
4.1%
Other values (20) 827
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2490
80.0%
Other Punctuation 541
 
17.4%
Dash Punctuation 75
 
2.4%
Decimal Number 4
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 376
15.1%
c 283
11.4%
n 237
9.5%
a 230
9.2%
o 228
9.2%
p 182
 
7.3%
e 147
 
5.9%
r 143
 
5.7%
h 102
 
4.1%
f 95
 
3.8%
Other values (14) 467
18.8%
Other Punctuation
ValueCountFrequency (%)
/ 330
61.0%
. 128
 
23.7%
: 83
 
15.3%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Decimal Number
ValueCountFrequency (%)
0 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2491
80.1%
Common 620
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 376
15.1%
c 283
11.4%
n 237
9.5%
a 230
9.2%
o 228
9.2%
p 182
 
7.3%
e 147
 
5.9%
r 143
 
5.7%
h 102
 
4.1%
f 95
 
3.8%
Other values (15) 468
18.8%
Common
ValueCountFrequency (%)
/ 330
53.2%
. 128
 
20.6%
: 83
 
13.4%
- 75
 
12.1%
0 4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 376
12.1%
/ 330
 
10.6%
c 283
 
9.1%
n 237
 
7.6%
a 230
 
7.4%
o 228
 
7.3%
p 182
 
5.9%
e 147
 
4.7%
r 143
 
4.6%
. 128
 
4.1%
Other values (20) 827
26.6%

NG Vehicle Class
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)0.2%
Missing68626
Missing (%)97.5%
Memory size550.2 KiB
HD
1489 
MD
254 
LD
 
37

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters3560
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMD
2nd rowMD
3rd rowLD
4th rowHD
5th rowMD

Common Values

ValueCountFrequency (%)
HD 1489
 
2.1%
MD 254
 
0.4%
LD 37
 
0.1%
(Missing) 68626
97.5%

Length

2023-08-29T04:26:09.272224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:09.569587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
hd 1489
83.7%
md 254
 
14.3%
ld 37
 
2.1%

Most occurring characters

ValueCountFrequency (%)
D 1780
50.0%
H 1489
41.8%
M 254
 
7.1%
L 37
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3560
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 1780
50.0%
H 1489
41.8%
M 254
 
7.1%
L 37
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3560
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 1780
50.0%
H 1489
41.8%
M 254
 
7.1%
L 37
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
D 1780
50.0%
H 1489
41.8%
M 254
 
7.1%
L 37
 
1.0%

LPG Primary
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing68539
Missing (%)97.3%
Memory size550.2 KiB
True
 
1867
(Missing)
68539 
ValueCountFrequency (%)
True 1867
 
2.7%
(Missing) 68539
97.3%
2023-08-29T04:26:09.848671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing65898
Missing (%)93.6%
Memory size550.2 KiB
False
 
2995
True
 
1513
(Missing)
65898 
ValueCountFrequency (%)
False 2995
 
4.3%
True 1513
 
2.1%
(Missing) 65898
93.6%
2023-08-29T04:26:10.088912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

EV Connector Types
Categorical

IMBALANCE  MISSING 

Distinct26
Distinct (%)< 0.1%
Missing9716
Missing (%)13.8%
Memory size550.2 KiB
J1772
47190 
CHADEMO J1772COMBO
 
4357
TESLA
 
3892
J1772 TESLA
 
2834
CHADEMO J1772 J1772COMBO
 
1061
Other values (21)
 
1356

Length

Max length32
Median length5
Mean length6.6980227
Min length5

Characters and Unicode

Total characters406503
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowCHADEMO J1772 J1772COMBO
2nd rowJ1772
3rd rowJ1772
4th rowCHADEMO J1772 J1772COMBO
5th rowCHADEMO J1772 J1772COMBO

Common Values

ValueCountFrequency (%)
J1772 47190
67.0%
CHADEMO J1772COMBO 4357
 
6.2%
TESLA 3892
 
5.5%
J1772 TESLA 2834
 
4.0%
CHADEMO J1772 J1772COMBO 1061
 
1.5%
J1772COMBO 519
 
0.7%
CHADEMO J1772 331
 
0.5%
J1772 J1772COMBO 134
 
0.2%
J1772 NEMA515 122
 
0.2%
CHADEMO 112
 
0.2%
Other values (16) 138
 
0.2%
(Missing) 9716
 
13.8%

Length

2023-08-29T04:26:10.462327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
j1772 51801
73.2%
tesla 6737
 
9.5%
j1772combo 6084
 
8.6%
chademo 5875
 
8.3%
nema515 125
 
0.2%
nema520 102
 
0.1%
nema1450 25
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
7 115770
28.5%
1 58035
14.3%
2 57987
14.3%
J 57885
14.2%
O 18043
 
4.4%
A 12864
 
3.2%
E 12864
 
3.2%
M 12211
 
3.0%
C 11959
 
2.9%
10059
 
2.5%
Other values (10) 38826
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 232321
57.2%
Uppercase Letter 164123
40.4%
Space Separator 10059
 
2.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
J 57885
35.3%
O 18043
 
11.0%
A 12864
 
7.8%
E 12864
 
7.8%
M 12211
 
7.4%
C 11959
 
7.3%
T 6737
 
4.1%
S 6737
 
4.1%
L 6737
 
4.1%
B 6084
 
3.7%
Other values (3) 12002
 
7.3%
Decimal Number
ValueCountFrequency (%)
7 115770
49.8%
1 58035
25.0%
2 57987
25.0%
5 377
 
0.2%
0 127
 
0.1%
4 25
 
< 0.1%
Space Separator
ValueCountFrequency (%)
10059
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242380
59.6%
Latin 164123
40.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
J 57885
35.3%
O 18043
 
11.0%
A 12864
 
7.8%
E 12864
 
7.8%
M 12211
 
7.4%
C 11959
 
7.3%
T 6737
 
4.1%
S 6737
 
4.1%
L 6737
 
4.1%
B 6084
 
3.7%
Other values (3) 12002
 
7.3%
Common
ValueCountFrequency (%)
7 115770
47.8%
1 58035
23.9%
2 57987
23.9%
10059
 
4.2%
5 377
 
0.2%
0 127
 
0.1%
4 25
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 406503
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 115770
28.5%
1 58035
14.3%
2 57987
14.3%
J 57885
14.2%
O 18043
 
4.4%
A 12864
 
3.2%
E 12864
 
3.2%
M 12211
 
3.0%
C 11959
 
2.9%
10059
 
2.5%
Other values (10) 38826
 
9.6%

Country
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
US
61621 
CA
8785 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters140812
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS

Common Values

ValueCountFrequency (%)
US 61621
87.5%
CA 8785
 
12.5%

Length

2023-08-29T04:26:10.807328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:11.206675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
us 61621
87.5%
ca 8785
 
12.5%

Most occurring characters

ValueCountFrequency (%)
U 61621
43.8%
S 61621
43.8%
C 8785
 
6.2%
A 8785
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 140812
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 61621
43.8%
S 61621
43.8%
C 8785
 
6.2%
A 8785
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 140812
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 61621
43.8%
S 61621
43.8%
C 8785
 
6.2%
A 8785
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 140812
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 61621
43.8%
S 61621
43.8%
C 8785
 
6.2%
A 8785
 
6.2%

Intersection Directions (French)
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct172
Distinct (%)91.5%
Missing70218
Missing (%)99.7%
Memory size550.2 KiB
112 St et 89 Ave
 
2
une unitée à l'intérieur; une unitée à  l'extérieur
 
2
Une unité à l'intérieur; une unité à l'extérieur
 
2
Côté nord du bâtiment
 
2
une unité à l'intérieur; deux unités à l'extérieur
 
2
Other values (167)
178 

Length

Max length169
Median length61
Mean length39.085106
Min length5

Characters and Unicode

Total characters7348
Distinct characters87
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique156 ?
Unique (%)83.0%

Sample

1st rowA coté de l'office d'automobile
2nd rowA l'arrière du batiment avec une entrée très atroite
3rd rowSituée sur le côté ouest du parc
4th rowQuai de chargement 2 -En arrière du batiment
5th row20 km à  l'ouest de Grand Falls-Windsor

Common Values

ValueCountFrequency (%)
112 St et 89 Ave 2
 
< 0.1%
une unitée à l'intérieur; une unitée à  l'extérieur 2
 
< 0.1%
Une unité à l'intérieur; une unité à l'extérieur 2
 
< 0.1%
Côté nord du bâtiment 2
 
< 0.1%
une unité à l'intérieur; deux unités à l'extérieur 2
 
< 0.1%
une unité à l'extérieur; deux unités à l'interieur 2
 
< 0.1%
Une unite a l'interieur, deux unites a l'exterieur 2
 
< 0.1%
1250 chemin Craig et 1287 chemin de la Coopérative 2
 
< 0.1%
Rue Stanley 2
 
< 0.1%
Entrez de la 14ème rue 2
 
< 0.1%
Other values (162) 168
 
0.2%
(Missing) 70218
99.7%

Length

2023-08-29T04:26:11.608734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de 80
 
6.1%
la 59
 
4.5%
et 52
 
4.0%
du 40
 
3.1%
rue 34
 
2.6%
à 34
 
2.6%
le 24
 
1.8%
une 24
 
1.8%
stationnement 22
 
1.7%
ã 21
 
1.6%
Other values (419) 919
70.2%

Most occurring characters

ValueCountFrequency (%)
1107
15.1%
e 844
 
11.5%
t 575
 
7.8%
r 445
 
6.1%
n 421
 
5.7%
u 410
 
5.6%
i 374
 
5.1%
a 340
 
4.6%
o 267
 
3.6%
l 257
 
3.5%
Other values (77) 2308
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5156
70.2%
Space Separator 1149
 
15.6%
Uppercase Letter 519
 
7.1%
Decimal Number 260
 
3.5%
Other Punctuation 147
 
2.0%
Other Symbol 61
 
0.8%
Currency Symbol 24
 
0.3%
Dash Punctuation 19
 
0.3%
Modifier Symbol 11
 
0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 844
16.4%
t 575
11.2%
r 445
8.6%
n 421
8.2%
u 410
8.0%
i 374
 
7.3%
a 340
 
6.6%
o 267
 
5.2%
l 257
 
5.0%
d 240
 
4.7%
Other values (21) 983
19.1%
Uppercase Letter
ValueCountFrequency (%)
S 96
18.5%
à 89
17.1%
A 56
10.8%
C 35
 
6.7%
N 28
 
5.4%
E 25
 
4.8%
P 23
 
4.4%
R 21
 
4.0%
I 14
 
2.7%
W 13
 
2.5%
Other values (17) 119
22.9%
Decimal Number
ValueCountFrequency (%)
1 64
24.6%
2 34
13.1%
0 31
11.9%
4 30
11.5%
3 24
 
9.2%
9 21
 
8.1%
5 17
 
6.5%
8 15
 
5.8%
7 12
 
4.6%
6 12
 
4.6%
Other Punctuation
ValueCountFrequency (%)
' 74
50.3%
, 36
24.5%
; 12
 
8.2%
. 10
 
6.8%
/ 6
 
4.1%
# 4
 
2.7%
& 3
 
2.0%
" 2
 
1.4%
Space Separator
ValueCountFrequency (%)
1107
96.3%
  42
 
3.7%
Other Symbol
ValueCountFrequency (%)
© 47
77.0%
14
 
23.0%
Currency Symbol
ValueCountFrequency (%)
18
75.0%
¢ 6
 
25.0%
Modifier Symbol
ValueCountFrequency (%)
´ 6
54.5%
¨ 5
45.5%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5675
77.2%
Common 1673
 
22.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 844
14.9%
t 575
 
10.1%
r 445
 
7.8%
n 421
 
7.4%
u 410
 
7.2%
i 374
 
6.6%
a 340
 
6.0%
o 267
 
4.7%
l 257
 
4.5%
d 240
 
4.2%
Other values (48) 1502
26.5%
Common
ValueCountFrequency (%)
1107
66.2%
' 74
 
4.4%
1 64
 
3.8%
© 47
 
2.8%
  42
 
2.5%
, 36
 
2.2%
2 34
 
2.0%
0 31
 
1.9%
4 30
 
1.8%
3 24
 
1.4%
Other values (19) 184
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6926
94.3%
None 390
 
5.3%
Currency Symbols 18
 
0.2%
Letterlike Symbols 14
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1107
16.0%
e 844
12.2%
t 575
 
8.3%
r 445
 
6.4%
n 421
 
6.1%
u 410
 
5.9%
i 374
 
5.4%
a 340
 
4.9%
o 267
 
3.9%
l 257
 
3.7%
Other values (61) 1886
27.2%
None
ValueCountFrequency (%)
é 96
24.6%
à 89
22.8%
© 47
12.1%
  42
10.8%
à 32
 
8.2%
è 26
 
6.7%
â 25
 
6.4%
 7
 
1.8%
´ 6
 
1.5%
¢ 6
 
1.5%
Other values (4) 14
 
3.6%
Currency Symbols
ValueCountFrequency (%)
18
100.0%
Letterlike Symbols
ValueCountFrequency (%)
14
100.0%

Access Days Time (French)
Categorical

HIGH CARDINALITY  IMBALANCE  MISSING 

Distinct755
Distinct (%)11.5%
Missing63815
Missing (%)90.6%
Memory size550.2 KiB
Accessible 24 heures par jour
4036 
24 heures par jour
762 
Accessible 24 heures par jour; réservé aux clients; rendez-vous à la réception pour avoir accès
 
191
Accessible 24 heures par jour; à l'usage des modèles Tesla seulement
 
123
Accessible 24 heures par jour; réservé aux clients
 
115
Other values (750)
1364 

Length

Max length193
Median length29
Mean length35.061144
Min length17

Characters and Unicode

Total characters231088
Distinct characters88
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique623 ?
Unique (%)9.5%

Sample

1st row24 heures par jour
2nd row24 heures par jour
3rd row24 heures par jour
4th row7:00-18:00 LUN-VEN, 8:00-14:00 SAT
5th row8:00-17:00 LUN-VEN; disponible au public le reste des heures et les fin de semaines

Common Values

ValueCountFrequency (%)
Accessible 24 heures par jour 4036
 
5.7%
24 heures par jour 762
 
1.1%
Accessible 24 heures par jour; réservé aux clients; rendez-vous à la réception pour avoir accès 191
 
0.3%
Accessible 24 heures par jour; à l'usage des modèles Tesla seulement 123
 
0.2%
Accessible 24 heures par jour; réservé aux clients 115
 
0.2%
6:00-22:00 tous les jours 36
 
0.1%
Accessible 24 heures par jour; réservé aux clients; pour avoir accès consulter le valet de stationnement 32
 
< 0.1%
Accessible 24 heures par jour; payer beaucoup 32
 
< 0.1%
Accessible 24 heures par jour; rendez-vous à la réception pour avoir accès 29
 
< 0.1%
8:00-17:00 LUN-VEN 26
 
< 0.1%
Other values (745) 1209
 
1.7%
(Missing) 63815
90.6%

Length

2023-08-29T04:26:12.120182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
heures 5781
15.1%
24 5692
14.8%
par 5686
14.8%
jour 5672
14.8%
accessible 4721
12.3%
clients 530
 
1.4%
pour 422
 
1.1%
seulement 421
 
1.1%
les 416
 
1.1%
à 409
 
1.1%
Other values (577) 8607
22.4%

Most occurring characters

ValueCountFrequency (%)
31762
13.7%
e 27900
 
12.1%
r 20312
 
8.8%
s 20184
 
8.7%
u 14678
 
6.4%
c 11841
 
5.1%
a 8709
 
3.8%
o 8645
 
3.7%
l 7766
 
3.4%
p 6968
 
3.0%
Other values (78) 72323
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 162906
70.5%
Space Separator 31845
 
13.8%
Decimal Number 19658
 
8.5%
Uppercase Letter 9945
 
4.3%
Other Punctuation 4494
 
1.9%
Dash Punctuation 1979
 
0.9%
Other Symbol 100
 
< 0.1%
Currency Symbol 50
 
< 0.1%
Modifier Symbol 36
 
< 0.1%
Open Punctuation 30
 
< 0.1%
Other values (3) 45
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 27900
17.1%
r 20312
12.5%
s 20184
12.4%
u 14678
9.0%
c 11841
7.3%
a 8709
 
5.3%
o 8645
 
5.3%
l 7766
 
4.8%
p 6968
 
4.3%
i 6797
 
4.2%
Other values (22) 29106
17.9%
Uppercase Letter
ValueCountFrequency (%)
A 5209
52.4%
N 761
 
7.7%
M 573
 
5.8%
U 463
 
4.7%
E 453
 
4.6%
L 441
 
4.4%
V 348
 
3.5%
S 328
 
3.3%
D 253
 
2.5%
I 244
 
2.5%
Other values (16) 872
 
8.8%
Decimal Number
ValueCountFrequency (%)
2 6662
33.9%
4 5729
29.1%
0 4525
23.0%
1 705
 
3.6%
7 581
 
3.0%
8 472
 
2.4%
3 391
 
2.0%
6 326
 
1.7%
9 184
 
0.9%
5 83
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 2255
50.2%
; 1378
30.7%
' 446
 
9.9%
, 396
 
8.8%
. 8
 
0.2%
/ 4
 
0.1%
" 3
 
0.1%
@ 3
 
0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31762
99.7%
  83
 
0.3%
Other Symbol
ValueCountFrequency (%)
© 60
60.0%
40
40.0%
Dash Punctuation
ValueCountFrequency (%)
- 1979
100.0%
Currency Symbol
ValueCountFrequency (%)
50
100.0%
Modifier Symbol
ValueCountFrequency (%)
¨ 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Math Symbol
ValueCountFrequency (%)
+ 13
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 172851
74.8%
Common 58237
 
25.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 27900
16.1%
r 20312
11.8%
s 20184
11.7%
u 14678
 
8.5%
c 11841
 
6.9%
a 8709
 
5.0%
o 8645
 
5.0%
l 7766
 
4.5%
p 6968
 
4.0%
i 6797
 
3.9%
Other values (48) 39051
22.6%
Common
ValueCountFrequency (%)
31762
54.5%
2 6662
 
11.4%
4 5729
 
9.8%
0 4525
 
7.8%
: 2255
 
3.9%
- 1979
 
3.4%
; 1378
 
2.4%
1 705
 
1.2%
7 581
 
1.0%
8 472
 
0.8%
Other values (20) 2189
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 228648
98.9%
None 2348
 
1.0%
Currency Symbols 50
 
< 0.1%
Letterlike Symbols 40
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31762
13.9%
e 27900
 
12.2%
r 20312
 
8.9%
s 20184
 
8.8%
u 14678
 
6.4%
c 11841
 
5.2%
a 8709
 
3.8%
o 8645
 
3.8%
l 7766
 
3.4%
p 6968
 
3.0%
Other values (62) 69883
30.6%
None
ValueCountFrequency (%)
é 1080
46.0%
è 424
 
18.1%
à 366
 
15.6%
à 171
 
7.3%
  83
 
3.5%
© 60
 
2.6%
À 43
 
1.8%
â 40
 
1.7%
Å 39
 
1.7%
¨ 36
 
1.5%
Other values (3) 6
 
0.3%
Currency Symbols
ValueCountFrequency (%)
50
100.0%
Letterlike Symbols
ValueCountFrequency (%)
40
100.0%
Punctuation
ValueCountFrequency (%)
2
100.0%

BD Blends (French)
Categorical

MISSING  UNIFORM 

Distinct2
Distinct (%)100.0%
Missing70404
Missing (%)> 99.9%
Memory size550.2 KiB
B100
B100, B50, B20

Length

Max length14
Median length9
Mean length9
Min length4

Characters and Unicode

Total characters18
Distinct characters7
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowB100
2nd rowB100, B50, B20

Common Values

ValueCountFrequency (%)
B100 1
 
< 0.1%
B100, B50, B20 1
 
< 0.1%
(Missing) 70404
> 99.9%

Length

2023-08-29T04:26:12.507277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:12.807187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b100 2
50.0%
b50 1
25.0%
b20 1
25.0%

Most occurring characters

ValueCountFrequency (%)
0 6
33.3%
B 4
22.2%
1 2
 
11.1%
, 2
 
11.1%
2
 
11.1%
5 1
 
5.6%
2 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
55.6%
Uppercase Letter 4
 
22.2%
Other Punctuation 2
 
11.1%
Space Separator 2
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
60.0%
1 2
 
20.0%
5 1
 
10.0%
2 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
77.8%
Latin 4
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6
42.9%
1 2
 
14.3%
, 2
 
14.3%
2
 
14.3%
5 1
 
7.1%
2 1
 
7.1%
Latin
ValueCountFrequency (%)
B 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
33.3%
B 4
22.2%
1 2
 
11.1%
, 2
 
11.1%
2
 
11.1%
5 1
 
5.6%
2 1
 
5.6%
Distinct28
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
Public
58045 
Privé
 
3849
Public - Carte de crédit en tout temps
 
3629
Public - Appeler à l'avance
 
1776
Privé - Réservé au gouvernement
 
939
Other values (23)
 
2168

Length

Max length79
Median length6
Mean length9.5763997
Min length5

Characters and Unicode

Total characters674236
Distinct characters43
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowPrivé
2nd rowPublic - Carte-clé en tout temps
3rd rowPrivé - Réservé au gouvernement
4th rowPrivé
5th rowPublic - Carte de crédit en tout temps

Common Values

ValueCountFrequency (%)
Public 58045
82.4%
Privé 3849
 
5.5%
Public - Carte de crédit en tout temps 3629
 
5.2%
Public - Appeler à l'avance 1776
 
2.5%
Privé - Réservé au gouvernement 939
 
1.3%
PRÉVU - pas encore accessible (Public) 795
 
1.1%
Public - Carte de crédit après les heures d'ouverture 539
 
0.8%
Public - Carte-clé en tout temps 214
 
0.3%
TEMPORAIREMENT SUSPENDU (Public) 144
 
0.2%
PRÉVU - pas encore accessible (Privé) 130
 
0.2%
Other values (18) 346
 
0.5%

Length

2023-08-29T04:26:13.256326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
public 65325
54.7%
8409
 
7.0%
privé 5081
 
4.3%
de 4388
 
3.7%
carte 4308
 
3.6%
crédit 4308
 
3.6%
en 3990
 
3.3%
tout 3990
 
3.3%
temps 3990
 
3.3%
appeler 1800
 
1.5%
Other values (22) 13875
 
11.6%

Most occurring characters

ValueCountFrequency (%)
i 75788
11.2%
c 74839
11.1%
u 73101
10.8%
P 71856
10.7%
l 70888
10.5%
b 66311
9.8%
49058
7.3%
e 33281
 
4.9%
t 22507
 
3.3%
r 21242
 
3.2%
Other values (33) 115365
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 523778
77.7%
Uppercase Letter 87863
 
13.0%
Space Separator 49058
 
7.3%
Dash Punctuation 8696
 
1.3%
Other Punctuation 2405
 
0.4%
Open Punctuation 1218
 
0.2%
Close Punctuation 1218
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 75788
14.5%
c 74839
14.3%
u 73101
14.0%
l 70888
13.5%
b 66311
12.7%
e 33281
6.4%
t 22507
 
4.3%
r 21242
 
4.1%
a 11877
 
2.3%
é 11728
 
2.2%
Other values (12) 62216
11.9%
Uppercase Letter
ValueCountFrequency (%)
P 71856
81.8%
C 4595
 
5.2%
R 2474
 
2.8%
A 2032
 
2.3%
U 1450
 
1.7%
É 986
 
1.1%
V 986
 
1.1%
E 929
 
1.1%
N 464
 
0.5%
S 464
 
0.5%
Other values (6) 1627
 
1.9%
Space Separator
ValueCountFrequency (%)
49058
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8696
100.0%
Other Punctuation
ValueCountFrequency (%)
' 2405
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 611641
90.7%
Common 62595
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 75788
12.4%
c 74839
12.2%
u 73101
12.0%
P 71856
11.7%
l 70888
11.6%
b 66311
10.8%
e 33281
 
5.4%
t 22507
 
3.7%
r 21242
 
3.5%
a 11877
 
1.9%
Other values (28) 89951
14.7%
Common
ValueCountFrequency (%)
49058
78.4%
- 8696
 
13.9%
' 2405
 
3.8%
( 1218
 
1.9%
) 1218
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 659117
97.8%
None 15119
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 75788
11.5%
c 74839
11.4%
u 73101
11.1%
P 71856
10.9%
l 70888
10.8%
b 66311
10.1%
49058
7.4%
e 33281
 
5.0%
t 22507
 
3.4%
r 21242
 
3.2%
Other values (29) 100246
15.2%
None
ValueCountFrequency (%)
é 11728
77.6%
à 1800
 
11.9%
É 986
 
6.5%
è 605
 
4.0%

Hydrogen Is Retail
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.9%
Missing70289
Missing (%)99.8%
Memory size550.2 KiB
True
 
117
(Missing)
70289 
ValueCountFrequency (%)
True 117
 
0.2%
(Missing) 70289
99.8%
2023-08-29T04:26:13.773262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Access Code
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size550.2 KiB
public
65325 
private
 
5081

Length

Max length7
Median length6
Mean length6.0721671
Min length6

Characters and Unicode

Total characters427517
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowprivate
2nd rowpublic
3rd rowprivate
4th rowprivate
5th rowpublic

Common Values

ValueCountFrequency (%)
public 65325
92.8%
private 5081
 
7.2%

Length

2023-08-29T04:26:14.153059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:14.513382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
public 65325
92.8%
private 5081
 
7.2%

Most occurring characters

ValueCountFrequency (%)
p 70406
16.5%
i 70406
16.5%
u 65325
15.3%
b 65325
15.3%
l 65325
15.3%
c 65325
15.3%
r 5081
 
1.2%
v 5081
 
1.2%
a 5081
 
1.2%
t 5081
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 427517
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 70406
16.5%
i 70406
16.5%
u 65325
15.3%
b 65325
15.3%
l 65325
15.3%
c 65325
15.3%
r 5081
 
1.2%
v 5081
 
1.2%
a 5081
 
1.2%
t 5081
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 427517
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 70406
16.5%
i 70406
16.5%
u 65325
15.3%
b 65325
15.3%
l 65325
15.3%
c 65325
15.3%
r 5081
 
1.2%
v 5081
 
1.2%
a 5081
 
1.2%
t 5081
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 427517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
p 70406
16.5%
i 70406
16.5%
u 65325
15.3%
b 65325
15.3%
l 65325
15.3%
c 65325
15.3%
r 5081
 
1.2%
v 5081
 
1.2%
a 5081
 
1.2%
t 5081
 
1.2%
Distinct9
Distinct (%)0.1%
Missing62983
Missing (%)89.5%
Memory size550.2 KiB
CREDIT_CARD_ALWAYS
3758 
CALL
1800 
GOVERNMENT
944 
CREDIT_CARD_AFTER_HOURS
550 
KEY_ALWAYS
 
232
Other values (4)
 
139

Length

Max length23
Median length18
Mean length13.542907
Min length4

Characters and Unicode

Total characters100529
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowKEY_ALWAYS
2nd rowGOVERNMENT
3rd rowCREDIT_CARD_ALWAYS
4th rowCREDIT_CARD_ALWAYS
5th rowCREDIT_CARD_ALWAYS

Common Values

ValueCountFrequency (%)
CREDIT_CARD_ALWAYS 3758
 
5.3%
CALL 1800
 
2.6%
GOVERNMENT 944
 
1.3%
CREDIT_CARD_AFTER_HOURS 550
 
0.8%
KEY_ALWAYS 232
 
0.3%
FLEET 80
 
0.1%
KEY_AFTER_HOURS 55
 
0.1%
LIMITED_HOURS 3
 
< 0.1%
RESIDENTIAL 1
 
< 0.1%
(Missing) 62983
89.5%

Length

2023-08-29T04:26:14.926106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:15.285776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
credit_card_always 3758
50.6%
call 1800
24.2%
government 944
 
12.7%
credit_card_after_hours 550
 
7.4%
key_always 232
 
3.1%
fleet 80
 
1.1%
key_after_hours 55
 
0.7%
limited_hours 3
 
< 0.1%
residential 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
A 14694
14.6%
R 10774
10.7%
C 10416
10.4%
_ 9511
9.5%
D 8620
8.6%
L 7674
7.6%
E 7253
7.2%
T 5941
 
5.9%
S 4599
 
4.6%
I 4316
 
4.3%
Other values (11) 16731
16.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 91018
90.5%
Connector Punctuation 9511
 
9.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 14694
16.1%
R 10774
11.8%
C 10416
11.4%
D 8620
9.5%
L 7674
8.4%
E 7253
8.0%
T 5941
6.5%
S 4599
 
5.1%
I 4316
 
4.7%
Y 4277
 
4.7%
Other values (10) 12454
13.7%
Connector Punctuation
ValueCountFrequency (%)
_ 9511
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 91018
90.5%
Common 9511
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 14694
16.1%
R 10774
11.8%
C 10416
11.4%
D 8620
9.5%
L 7674
8.4%
E 7253
8.0%
T 5941
6.5%
S 4599
 
5.1%
I 4316
 
4.7%
Y 4277
 
4.7%
Other values (10) 12454
13.7%
Common
ValueCountFrequency (%)
_ 9511
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100529
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 14694
14.6%
R 10774
10.7%
C 10416
10.4%
_ 9511
9.5%
D 8620
8.6%
L 7674
7.6%
E 7253
7.2%
T 5941
 
5.9%
S 4599
 
4.6%
I 4316
 
4.3%
Other values (11) 16731
16.6%
Distinct26
Distinct (%)2.7%
Missing69451
Missing (%)98.6%
Memory size550.2 KiB
DON
200 
DOI
134 
DOE
126 
USMC
78 
DAF
69 
Other values (21)
348 

Length

Max length8
Median length3
Mean length3.0544503
Min length2

Characters and Unicode

Total characters2917
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st rowUSMC
2nd rowDOI
3rd rowDAF
4th rowDAF
5th rowDAF

Common Values

ValueCountFrequency (%)
DON 200
 
0.3%
DOI 134
 
0.2%
DOE 126
 
0.2%
USMC 78
 
0.1%
DAF 69
 
0.1%
DA 58
 
0.1%
VA 58
 
0.1%
DOT 27
 
< 0.1%
DOJ 24
 
< 0.1%
NASA 24
 
< 0.1%
Other values (16) 157
 
0.2%
(Missing) 69451
98.6%

Length

2023-08-29T04:26:15.776211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
don 200
20.9%
doi 134
14.0%
doe 126
13.2%
usmc 78
 
8.2%
daf 69
 
7.2%
da 58
 
6.1%
va 58
 
6.1%
dot 27
 
2.8%
doj 24
 
2.5%
nasa 24
 
2.5%
Other values (16) 157
16.4%

Most occurring characters

ValueCountFrequency (%)
D 722
24.8%
O 529
18.1%
A 291
10.0%
S 240
 
8.2%
N 225
 
7.7%
E 162
 
5.6%
I 146
 
5.0%
U 126
 
4.3%
C 100
 
3.4%
F 83
 
2.8%
Other values (11) 293
10.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2910
99.8%
Connector Punctuation 7
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 722
24.8%
O 529
18.2%
A 291
10.0%
S 240
 
8.2%
N 225
 
7.7%
E 162
 
5.6%
I 146
 
5.0%
U 126
 
4.3%
C 100
 
3.4%
F 83
 
2.9%
Other values (10) 286
 
9.8%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2910
99.8%
Common 7
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 722
24.8%
O 529
18.2%
A 291
10.0%
S 240
 
8.2%
N 225
 
7.7%
E 162
 
5.6%
I 146
 
5.0%
U 126
 
4.3%
C 100
 
3.4%
F 83
 
2.9%
Other values (10) 286
 
9.8%
Common
ValueCountFrequency (%)
_ 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2917
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
D 722
24.8%
O 529
18.1%
A 291
10.0%
S 240
 
8.2%
N 225
 
7.7%
E 162
 
5.6%
I 146
 
5.0%
U 126
 
4.3%
C 100
 
3.4%
F 83
 
2.8%
Other values (11) 293
10.0%

Facility Type
Categorical

HIGH CARDINALITY  MISSING 

Distinct62
Distinct (%)0.2%
Missing42741
Missing (%)60.7%
Memory size550.2 KiB
CONVENIENCE_STORE
4951 
HOTEL
3133 
CAR_DEALER
2885 
MUNI_GOV
 
1217
SHOPPING_CENTER
 
1151
Other values (57)
14328 

Length

Max length25
Median length17
Mean length11.349286
Min length3

Characters and Unicode

Total characters313978
Distinct characters23
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSTANDALONE_STATION
2nd rowSTANDALONE_STATION
3rd rowFLEET_GARAGE
4th rowSTANDALONE_STATION
5th rowUTILITY

Common Values

ValueCountFrequency (%)
CONVENIENCE_STORE 4951
 
7.0%
HOTEL 3133
 
4.4%
CAR_DEALER 2885
 
4.1%
MUNI_GOV 1217
 
1.7%
SHOPPING_CENTER 1151
 
1.6%
OFFICE_BLDG 1037
 
1.5%
GAS_STATION 853
 
1.2%
UTILITY 826
 
1.2%
FUEL_RESELLER 797
 
1.1%
GROCERY 667
 
0.9%
Other values (52) 10148
 
14.4%
(Missing) 42741
60.7%

Length

2023-08-29T04:26:16.308779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
convenience_store 4951
17.9%
hotel 3133
 
11.3%
car_dealer 2885
 
10.4%
muni_gov 1217
 
4.4%
shopping_center 1151
 
4.2%
office_bldg 1037
 
3.7%
gas_station 853
 
3.1%
utility 826
 
3.0%
fuel_reseller 797
 
2.9%
grocery 667
 
2.4%
Other values (52) 10148
36.7%

Most occurring characters

ValueCountFrequency (%)
E 46901
14.9%
N 27438
 
8.7%
R 25185
 
8.0%
O 24544
 
7.8%
T 22334
 
7.1%
_ 21703
 
6.9%
A 20051
 
6.4%
C 18908
 
6.0%
L 17640
 
5.6%
I 16896
 
5.4%
Other values (13) 72378
23.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 292275
93.1%
Connector Punctuation 21703
 
6.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 46901
16.0%
N 27438
9.4%
R 25185
8.6%
O 24544
8.4%
T 22334
 
7.6%
A 20051
 
6.9%
C 18908
 
6.5%
L 17640
 
6.0%
I 16896
 
5.8%
S 13775
 
4.7%
Other values (12) 58603
20.1%
Connector Punctuation
ValueCountFrequency (%)
_ 21703
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 292275
93.1%
Common 21703
 
6.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 46901
16.0%
N 27438
9.4%
R 25185
8.6%
O 24544
8.4%
T 22334
 
7.6%
A 20051
 
6.9%
C 18908
 
6.5%
L 17640
 
6.0%
I 16896
 
5.8%
S 13775
 
4.7%
Other values (12) 58603
20.1%
Common
ValueCountFrequency (%)
_ 21703
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 313978
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 46901
14.9%
N 27438
 
8.7%
R 25185
 
8.0%
O 24544
 
7.8%
T 22334
 
7.1%
_ 21703
 
6.9%
A 20051
 
6.4%
C 18908
 
6.0%
L 17640
 
5.6%
I 16896
 
5.4%
Other values (13) 72378
23.1%

CNG Dispenser Num
Real number (ℝ)

Distinct26
Distinct (%)2.5%
Missing69367
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean2.7314726
Minimum0
Maximum202
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size550.2 KiB
2023-08-29T04:26:16.684211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum202
Range202
Interquartile range (IQR)1

Descriptive statistics

Standard deviation8.3334921
Coefficient of variation (CV)3.0509156
Kurtosis336.78074
Mean2.7314726
Median Absolute Deviation (MAD)1
Skewness16.151154
Sum2838
Variance69.447091
MonotonicityNot monotonic
2023-08-29T04:26:17.079303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 417
 
0.6%
2 415
 
0.6%
3 86
 
0.1%
4 85
 
0.1%
6 4
 
< 0.1%
12 4
 
< 0.1%
5 4
 
< 0.1%
8 3
 
< 0.1%
40 2
 
< 0.1%
80 2
 
< 0.1%
Other values (16) 17
 
< 0.1%
(Missing) 69367
98.5%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 417
0.6%
2 415
0.6%
3 86
 
0.1%
4 85
 
0.1%
5 4
 
< 0.1%
6 4
 
< 0.1%
7 2
 
< 0.1%
8 3
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
202 1
< 0.1%
80 2
< 0.1%
70 1
< 0.1%
52 1
< 0.1%
49 1
< 0.1%
47 1
< 0.1%
45 1
< 0.1%
40 2
< 0.1%
31 1
< 0.1%
26 1
< 0.1%

CNG On-Site Renewable Source
Categorical

IMBALANCE  MISSING 

Distinct5
Distinct (%)0.7%
Missing69690
Missing (%)99.0%
Memory size550.2 KiB
NONE
695 
LANDFILL
 
14
WASTEWATER
 
3
SOLAR
 
3
LIVESTOCK
 
1

Length

Max length10
Median length4
Mean length4.1145251
Min length4

Characters and Unicode

Total characters2946
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowNONE
2nd rowNONE
3rd rowNONE
4th rowNONE
5th rowNONE

Common Values

ValueCountFrequency (%)
NONE 695
 
1.0%
LANDFILL 14
 
< 0.1%
WASTEWATER 3
 
< 0.1%
SOLAR 3
 
< 0.1%
LIVESTOCK 1
 
< 0.1%
(Missing) 69690
99.0%

Length

2023-08-29T04:26:17.594115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:17.975054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
none 695
97.1%
landfill 14
 
2.0%
wastewater 3
 
0.4%
solar 3
 
0.4%
livestock 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
N 1404
47.7%
E 702
23.8%
O 699
23.7%
L 46
 
1.6%
A 23
 
0.8%
I 15
 
0.5%
D 14
 
0.5%
F 14
 
0.5%
S 7
 
0.2%
T 7
 
0.2%
Other values (5) 15
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2946
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1404
47.7%
E 702
23.8%
O 699
23.7%
L 46
 
1.6%
A 23
 
0.8%
I 15
 
0.5%
D 14
 
0.5%
F 14
 
0.5%
S 7
 
0.2%
T 7
 
0.2%
Other values (5) 15
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 2946
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1404
47.7%
E 702
23.8%
O 699
23.7%
L 46
 
1.6%
A 23
 
0.8%
I 15
 
0.5%
D 14
 
0.5%
F 14
 
0.5%
S 7
 
0.2%
T 7
 
0.2%
Other values (5) 15
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2946
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1404
47.7%
E 702
23.8%
O 699
23.7%
L 46
 
1.6%
A 23
 
0.8%
I 15
 
0.5%
D 14
 
0.5%
F 14
 
0.5%
S 7
 
0.2%
T 7
 
0.2%
Other values (5) 15
 
0.5%
Distinct213
Distinct (%)30.1%
Missing69698
Missing (%)99.0%
Infinite0
Infinite (%)0.0%
Mean873.76695
Minimum2
Maximum10620
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size550.2 KiB
2023-08-29T04:26:18.336473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile50
Q1215.75
median632
Q31100
95-th percentile2793
Maximum10620
Range10618
Interquartile range (IQR)884.25

Descriptive statistics

Standard deviation1032.3715
Coefficient of variation (CV)1.1815181
Kurtosis21.182727
Mean873.76695
Median Absolute Deviation (MAD)432
Skewness3.6295391
Sum618627
Variance1065790.8
MonotonicityNot monotonic
2023-08-29T04:26:18.891017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1400 44
 
0.1%
1000 39
 
0.1%
500 24
 
< 0.1%
975 24
 
< 0.1%
300 22
 
< 0.1%
100 20
 
< 0.1%
400 20
 
< 0.1%
50 19
 
< 0.1%
25 17
 
< 0.1%
150 16
 
< 0.1%
Other values (203) 463
 
0.7%
(Missing) 69698
99.0%
ValueCountFrequency (%)
2 2
 
< 0.1%
10 1
 
< 0.1%
18 1
 
< 0.1%
25 17
< 0.1%
28 4
 
< 0.1%
30 7
 
< 0.1%
35 1
 
< 0.1%
50 19
< 0.1%
56 1
 
< 0.1%
58 2
 
< 0.1%
ValueCountFrequency (%)
10620 1
< 0.1%
8250 1
< 0.1%
8000 1
< 0.1%
6600 1
< 0.1%
5700 1
< 0.1%
5400 1
< 0.1%
5376 1
< 0.1%
5000 2
< 0.1%
4701 1
< 0.1%
4400 1
< 0.1%

CNG Storage Capacity
Real number (ℝ)

Distinct155
Distinct (%)43.4%
Missing70049
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean47866.787
Minimum0
Maximum593136
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size550.2 KiB
2023-08-29T04:26:19.406386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile800
Q130000
median36000
Q360000
95-th percentile103480
Maximum593136
Range593136
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation54327.699
Coefficient of variation (CV)1.1349769
Kurtosis54.853268
Mean47866.787
Median Absolute Deviation (MAD)13200
Skewness6.3572428
Sum17088443
Variance2.9514989 × 109
MonotonicityNot monotonic
2023-08-29T04:26:20.097206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36000 46
 
0.1%
33000 23
 
< 0.1%
28125 12
 
< 0.1%
72000 12
 
< 0.1%
30000 11
 
< 0.1%
60000 11
 
< 0.1%
34713 8
 
< 0.1%
37000 8
 
< 0.1%
66000 7
 
< 0.1%
69426 7
 
< 0.1%
Other values (145) 212
 
0.3%
(Missing) 70049
99.5%
ValueCountFrequency (%)
0 4
< 0.1%
44 2
< 0.1%
74 1
 
< 0.1%
77 1
 
< 0.1%
100 2
< 0.1%
106 1
 
< 0.1%
134 1
 
< 0.1%
190 1
 
< 0.1%
205 1
 
< 0.1%
225 1
 
< 0.1%
ValueCountFrequency (%)
593136 1
< 0.1%
560000 1
< 0.1%
400000 1
< 0.1%
250000 1
< 0.1%
207598 1
< 0.1%
200000 1
< 0.1%
180855 1
< 0.1%
159000 1
< 0.1%
150000 1
< 0.1%
130000 1
< 0.1%

LNG On-Site Renewable Source
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.6%
Missing70344
Missing (%)99.9%
Memory size550.2 KiB
NONE
62 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters248
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNONE
2nd rowNONE
3rd rowNONE
4th rowNONE
5th rowNONE

Common Values

ValueCountFrequency (%)
NONE 62
 
0.1%
(Missing) 70344
99.9%

Length

2023-08-29T04:26:20.605568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:20.940073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
none 62
100.0%

Most occurring characters

ValueCountFrequency (%)
N 124
50.0%
O 62
25.0%
E 62
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 248
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 124
50.0%
O 62
25.0%
E 62
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 248
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 124
50.0%
O 62
25.0%
E 62
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 124
50.0%
O 62
25.0%
E 62
25.0%

E85 Other Ethanol Blends
Categorical

IMBALANCE  MISSING 

Distinct15
Distinct (%)1.0%
Missing68948
Missing (%)97.9%
Memory size550.2 KiB
["E15"]
1117 
["E15", "E30-E35"]
126 
["E30-E35"]
 
83
["E40-Plus"]
 
26
["E15", "E20-E25", "E30-E35"]
 
26
Other values (10)
 
80

Length

Max length41
Median length7
Mean length9.6282579
Min length7

Characters and Unicode

Total characters14038
Distinct characters17
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row["E15"]
2nd row["E15"]
3rd row["E15"]
4th row["E30-E35"]
5th row["E30-E35"]

Common Values

ValueCountFrequency (%)
["E15"] 1117
 
1.6%
["E15", "E30-E35"] 126
 
0.2%
["E30-E35"] 83
 
0.1%
["E40-Plus"] 26
 
< 0.1%
["E15", "E20-E25", "E30-E35"] 26
 
< 0.1%
["E20-E25", "E30-E35"] 17
 
< 0.1%
["E20-E25"] 13
 
< 0.1%
["E20-E25", "E30-E35", "E40-Plus"] 11
 
< 0.1%
["E15", "E20-E25", "E30-E35", "E40-Plus"] 10
 
< 0.1%
["E15", "E30-E35", "E40-Plus"] 7
 
< 0.1%
Other values (5) 22
 
< 0.1%
(Missing) 68948
97.9%

Length

2023-08-29T04:26:21.434546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
e15 1301
74.6%
e30-e35 286
 
16.4%
e20-e25 87
 
5.0%
e40-plus 69
 
4.0%

Most occurring characters

ValueCountFrequency (%)
" 3486
24.8%
E 2116
15.1%
5 1674
11.9%
[ 1458
10.4%
] 1458
10.4%
1 1301
 
9.3%
3 572
 
4.1%
0 442
 
3.1%
- 442
 
3.1%
285
 
2.0%
Other values (7) 804
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4232
30.1%
Other Punctuation 3771
26.9%
Uppercase Letter 2185
15.6%
Open Punctuation 1458
 
10.4%
Close Punctuation 1458
 
10.4%
Dash Punctuation 442
 
3.1%
Space Separator 285
 
2.0%
Lowercase Letter 207
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1674
39.6%
1 1301
30.7%
3 572
 
13.5%
0 442
 
10.4%
2 174
 
4.1%
4 69
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
l 69
33.3%
u 69
33.3%
s 69
33.3%
Other Punctuation
ValueCountFrequency (%)
" 3486
92.4%
, 285
 
7.6%
Uppercase Letter
ValueCountFrequency (%)
E 2116
96.8%
P 69
 
3.2%
Open Punctuation
ValueCountFrequency (%)
[ 1458
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1458
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 442
100.0%
Space Separator
ValueCountFrequency (%)
285
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11646
83.0%
Latin 2392
 
17.0%

Most frequent character per script

Common
ValueCountFrequency (%)
" 3486
29.9%
5 1674
14.4%
[ 1458
12.5%
] 1458
12.5%
1 1301
 
11.2%
3 572
 
4.9%
0 442
 
3.8%
- 442
 
3.8%
285
 
2.4%
, 285
 
2.4%
Other values (2) 243
 
2.1%
Latin
ValueCountFrequency (%)
E 2116
88.5%
P 69
 
2.9%
l 69
 
2.9%
u 69
 
2.9%
s 69
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14038
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 3486
24.8%
E 2116
15.1%
5 1674
11.9%
[ 1458
10.4%
] 1458
10.4%
1 1301
 
9.3%
3 572
 
4.1%
0 442
 
3.1%
- 442
 
3.1%
285
 
2.0%
Other values (7) 804
 
5.7%

EV Pricing
Categorical

HIGH CARDINALITY  IMBALANCE  MISSING 

Distinct749
Distinct (%)4.4%
Missing53445
Missing (%)75.9%
Memory size550.2 KiB
Free
10377 
$0.28 per kWh; $0.26 per minute above 60 kW and $0.13 per minute at or below 60 kW
1155 
FREE
1122 
Level 2: $0.49 per kWh
 
785
Level 2: $0.59 per kWh
 
303
Other values (744)
3219 

Length

Max length159
Median length4
Mean length15.574612
Min length3

Characters and Unicode

Total characters264161
Distinct characters75
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique484 ?
Unique (%)2.9%

Sample

1st rowFree
2nd rowFree
3rd rowPay to Park
4th rowFree
5th rowFree

Common Values

ValueCountFrequency (%)
Free 10377
 
14.7%
$0.28 per kWh; $0.26 per minute above 60 kW and $0.13 per minute at or below 60 kW 1155
 
1.6%
FREE 1122
 
1.6%
Level 2: $0.49 per kWh 785
 
1.1%
Level 2: $0.59 per kWh 303
 
0.4%
$2.00/Hr Parking Fee 222
 
0.3%
Level 2: $0.03 per 30 seconds 199
 
0.3%
$0.44 per minute above 60 kW and $0.22 per minute at or below 60 kW 123
 
0.2%
$1.00/Hr Parking Fee 100
 
0.1%
$1 initiation fee + $0.32 per minute 88
 
0.1%
Other values (739) 2487
 
3.5%
(Missing) 53445
75.9%

Length

2023-08-29T04:26:22.132219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
free 11751
21.3%
per 6589
 
11.9%
minute 2822
 
5.1%
kwh 2745
 
5.0%
kw 2560
 
4.6%
60 2557
 
4.6%
fee 1751
 
3.2%
2 1629
 
3.0%
level 1555
 
2.8%
or 1399
 
2.5%
Other values (593) 19783
35.9%

Most occurring characters

ValueCountFrequency (%)
e 41900
15.9%
38174
14.5%
r 23384
 
8.9%
0 13366
 
5.1%
F 13347
 
5.1%
$ 9064
 
3.4%
. 8380
 
3.2%
a 7345
 
2.8%
p 7103
 
2.7%
n 7076
 
2.7%
Other values (65) 95022
36.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 140935
53.4%
Space Separator 38174
 
14.5%
Decimal Number 33569
 
12.7%
Uppercase Letter 27969
 
10.6%
Other Punctuation 13534
 
5.1%
Currency Symbol 9064
 
3.4%
Dash Punctuation 724
 
0.3%
Math Symbol 158
 
0.1%
Control 14
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Other values (4) 14
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 41900
29.7%
r 23384
16.6%
a 7345
 
5.2%
p 7103
 
5.0%
n 7076
 
5.0%
k 6926
 
4.9%
i 6143
 
4.4%
o 5997
 
4.3%
t 5249
 
3.7%
h 4056
 
2.9%
Other values (14) 25756
18.3%
Uppercase Letter
ValueCountFrequency (%)
F 13347
47.7%
W 5617
20.1%
E 2616
 
9.4%
L 1655
 
5.9%
P 1220
 
4.4%
R 1152
 
4.1%
H 1151
 
4.1%
V 680
 
2.4%
C 210
 
0.8%
D 200
 
0.7%
Other values (12) 121
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 13366
39.8%
2 5339
 
15.9%
6 3791
 
11.3%
1 2796
 
8.3%
3 2265
 
6.7%
9 1647
 
4.9%
5 1607
 
4.8%
4 1345
 
4.0%
8 1239
 
3.7%
7 174
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 8380
61.9%
: 1838
 
13.6%
; 1544
 
11.4%
/ 1466
 
10.8%
, 304
 
2.2%
' 1
 
< 0.1%
& 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 157
99.4%
| 1
 
0.6%
Control
ValueCountFrequency (%)
7
50.0%
7
50.0%
Space Separator
ValueCountFrequency (%)
38174
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 9064
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 724
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%
Final Punctuation
ValueCountFrequency (%)
3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 168904
63.9%
Common 95257
36.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 41900
24.8%
r 23384
13.8%
F 13347
 
7.9%
a 7345
 
4.3%
p 7103
 
4.2%
n 7076
 
4.2%
k 6926
 
4.1%
i 6143
 
3.6%
o 5997
 
3.6%
W 5617
 
3.3%
Other values (36) 44066
26.1%
Common
ValueCountFrequency (%)
38174
40.1%
0 13366
 
14.0%
$ 9064
 
9.5%
. 8380
 
8.8%
2 5339
 
5.6%
6 3791
 
4.0%
1 2796
 
2.9%
3 2265
 
2.4%
: 1838
 
1.9%
9 1647
 
1.7%
Other values (19) 8597
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 264155
> 99.9%
Letterlike Symbols 3
 
< 0.1%
Punctuation 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 41900
15.9%
38174
14.5%
r 23384
 
8.9%
0 13366
 
5.1%
F 13347
 
5.1%
$ 9064
 
3.4%
. 8380
 
3.2%
a 7345
 
2.8%
p 7103
 
2.7%
n 7076
 
2.7%
Other values (63) 95016
36.0%
Letterlike Symbols
ValueCountFrequency (%)
3
100.0%
Punctuation
ValueCountFrequency (%)
3
100.0%

EV Pricing (French)
Categorical

HIGH CARDINALITY  IMBALANCE  MISSING 

Distinct140
Distinct (%)6.9%
Missing68374
Missing (%)97.1%
Memory size550.2 KiB
Gratuit
1499 
$0.44 par minute au-dessus de 60 kW et $0.22 par minute à 60 kW ou moins
 
123
L2: 1,50 $ de l'heure; DC Fast: 15,00 $ de l'heure
 
62
$1,50 par heure
 
45
$0,21 par minute
 
28
Other values (135)
275 

Length

Max length122
Median length7
Mean length15.295276
Min length4

Characters and Unicode

Total characters31080
Distinct characters73
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)5.0%

Sample

1st rowGratuit
2nd rowGratuit
3rd rowGratuit
4th rowGratuit
5th rowGratuit

Common Values

ValueCountFrequency (%)
Gratuit 1499
 
2.1%
$0.44 par minute au-dessus de 60 kW et $0.22 par minute à 60 kW ou moins 123
 
0.2%
L2: 1,50 $ de l'heure; DC Fast: 15,00 $ de l'heure 62
 
0.1%
$1,50 par heure 45
 
0.1%
$0,21 par minute 28
 
< 0.1%
$0.33 par minute 27
 
< 0.1%
0,30 $ par minute 20
 
< 0.1%
1$ par heure 13
 
< 0.1%
Gratuit; frais de stationnement requis 11
 
< 0.1%
$0.27 par minute 10
 
< 0.1%
Other values (130) 194
 
0.3%
(Missing) 68374
97.1%

Length

2023-08-29T04:26:22.874758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
gratuit 1570
27.3%
par 521
 
9.1%
minute 375
 
6.5%
de 333
 
5.8%
60 246
 
4.3%
kw 246
 
4.3%
181
 
3.1%
l'heure 147
 
2.6%
ou 124
 
2.2%
et 124
 
2.2%
Other values (158) 1884
32.8%

Most occurring characters

ValueCountFrequency (%)
t 3911
12.6%
3718
12.0%
u 2728
 
8.8%
r 2603
 
8.4%
a 2522
 
8.1%
i 2295
 
7.4%
e 1841
 
5.9%
G 1566
 
5.0%
0 944
 
3.0%
s 865
 
2.8%
Other values (63) 8087
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20732
66.7%
Space Separator 3719
 
12.0%
Decimal Number 2542
 
8.2%
Uppercase Letter 2208
 
7.1%
Other Punctuation 1054
 
3.4%
Currency Symbol 682
 
2.2%
Dash Punctuation 129
 
0.4%
Math Symbol 5
 
< 0.1%
Control 4
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 3911
18.9%
u 2728
13.2%
r 2603
12.6%
a 2522
12.2%
i 2295
11.1%
e 1841
8.9%
s 865
 
4.2%
n 705
 
3.4%
p 621
 
3.0%
m 578
 
2.8%
Other values (18) 2063
10.0%
Uppercase Letter
ValueCountFrequency (%)
G 1566
70.9%
W 247
 
11.2%
F 110
 
5.0%
D 92
 
4.2%
C 89
 
4.0%
L 79
 
3.6%
P 6
 
0.3%
N 4
 
0.2%
T 4
 
0.2%
S 3
 
0.1%
Other values (8) 8
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 944
37.1%
2 436
17.2%
1 276
 
10.9%
4 260
 
10.2%
6 256
 
10.1%
5 217
 
8.5%
3 128
 
5.0%
7 13
 
0.5%
8 7
 
0.3%
9 5
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 319
30.3%
, 280
26.6%
: 169
16.0%
' 152
14.4%
; 133
12.6%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
3718
> 99.9%
  1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 4
80.0%
| 1
 
20.0%
Control
ValueCountFrequency (%)
2
50.0%
2
50.0%
Currency Symbol
ValueCountFrequency (%)
$ 682
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Symbol
ValueCountFrequency (%)
© 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22940
73.8%
Common 8140
 
26.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 3911
17.0%
u 2728
11.9%
r 2603
11.3%
a 2522
11.0%
i 2295
10.0%
e 1841
8.0%
G 1566
6.8%
s 865
 
3.8%
n 705
 
3.1%
p 621
 
2.7%
Other values (36) 3283
14.3%
Common
ValueCountFrequency (%)
3718
45.7%
0 944
 
11.6%
$ 682
 
8.4%
2 436
 
5.4%
. 319
 
3.9%
, 280
 
3.4%
1 276
 
3.4%
4 260
 
3.2%
6 256
 
3.1%
5 217
 
2.7%
Other values (17) 752
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30908
99.4%
None 172
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 3911
12.7%
3718
12.0%
u 2728
 
8.8%
r 2603
 
8.4%
a 2522
 
8.2%
i 2295
 
7.4%
e 1841
 
6.0%
G 1566
 
5.1%
0 944
 
3.1%
s 865
 
2.8%
Other values (56) 7915
25.6%
None
ValueCountFrequency (%)
à 123
71.5%
é 26
 
15.1%
è 18
 
10.5%
ô 2
 
1.2%
  1
 
0.6%
à 1
 
0.6%
© 1
 
0.6%

LPG Nozzle Types
Categorical

Distinct4
Distinct (%)0.2%
Missing68580
Missing (%)97.4%
Memory size550.2 KiB
["ACME"]
1007 
["QUICK_CONNECT", "ACME"]
511 
["ACME", "QUICK_CONNECT"]
223 
["QUICK_CONNECT"]
 
85

Length

Max length25
Median length8
Mean length15.252464
Min length8

Characters and Unicode

Total characters27851
Distinct characters17
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row["ACME"]
2nd row["ACME"]
3rd row["ACME", "QUICK_CONNECT"]
4th row["ACME"]
5th row["ACME"]

Common Values

ValueCountFrequency (%)
["ACME"] 1007
 
1.4%
["QUICK_CONNECT", "ACME"] 511
 
0.7%
["ACME", "QUICK_CONNECT"] 223
 
0.3%
["QUICK_CONNECT"] 85
 
0.1%
(Missing) 68580
97.4%

Length

2023-08-29T04:26:23.457214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:23.889140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
acme 1741
68.0%
quick_connect 819
32.0%

Most occurring characters

ValueCountFrequency (%)
" 5120
18.4%
C 4198
15.1%
E 2560
9.2%
[ 1826
 
6.6%
] 1826
 
6.6%
A 1741
 
6.3%
M 1741
 
6.3%
N 1638
 
5.9%
_ 819
 
2.9%
T 819
 
2.9%
Other values (7) 5563
20.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 16792
60.3%
Other Punctuation 5854
 
21.0%
Open Punctuation 1826
 
6.6%
Close Punctuation 1826
 
6.6%
Connector Punctuation 819
 
2.9%
Space Separator 734
 
2.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 4198
25.0%
E 2560
15.2%
A 1741
10.4%
M 1741
10.4%
N 1638
 
9.8%
T 819
 
4.9%
O 819
 
4.9%
U 819
 
4.9%
K 819
 
4.9%
I 819
 
4.9%
Other Punctuation
ValueCountFrequency (%)
" 5120
87.5%
, 734
 
12.5%
Open Punctuation
ValueCountFrequency (%)
[ 1826
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1826
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 819
100.0%
Space Separator
ValueCountFrequency (%)
734
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16792
60.3%
Common 11059
39.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 4198
25.0%
E 2560
15.2%
A 1741
10.4%
M 1741
10.4%
N 1638
 
9.8%
T 819
 
4.9%
O 819
 
4.9%
U 819
 
4.9%
K 819
 
4.9%
I 819
 
4.9%
Common
ValueCountFrequency (%)
" 5120
46.3%
[ 1826
 
16.5%
] 1826
 
16.5%
_ 819
 
7.4%
, 734
 
6.6%
734
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27851
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 5120
18.4%
C 4198
15.1%
E 2560
9.2%
[ 1826
 
6.6%
] 1826
 
6.6%
A 1741
 
6.3%
M 1741
 
6.3%
N 1638
 
5.9%
_ 819
 
2.9%
T 819
 
2.9%
Other values (7) 5563
20.0%
Distinct2
Distinct (%)1.7%
Missing70290
Missing (%)99.8%
Memory size550.2 KiB
["700"]
71 
["350", "700"]
45 

Length

Max length14
Median length7
Mean length9.7155172
Min length7

Characters and Unicode

Total characters1127
Distinct characters9
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row["350", "700"]
2nd row["350", "700"]
3rd row["350", "700"]
4th row["700"]
5th row["700"]

Common Values

ValueCountFrequency (%)
["700"] 71
 
0.1%
["350", "700"] 45
 
0.1%
(Missing) 70290
99.8%

Length

2023-08-29T04:26:24.234254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:24.707853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
700 116
72.0%
350 45
 
28.0%

Most occurring characters

ValueCountFrequency (%)
" 322
28.6%
0 277
24.6%
[ 116
 
10.3%
7 116
 
10.3%
] 116
 
10.3%
3 45
 
4.0%
5 45
 
4.0%
, 45
 
4.0%
45
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 483
42.9%
Other Punctuation 367
32.6%
Open Punctuation 116
 
10.3%
Close Punctuation 116
 
10.3%
Space Separator 45
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 277
57.3%
7 116
24.0%
3 45
 
9.3%
5 45
 
9.3%
Other Punctuation
ValueCountFrequency (%)
" 322
87.7%
, 45
 
12.3%
Open Punctuation
ValueCountFrequency (%)
[ 116
100.0%
Close Punctuation
ValueCountFrequency (%)
] 116
100.0%
Space Separator
ValueCountFrequency (%)
45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1127
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
" 322
28.6%
0 277
24.6%
[ 116
 
10.3%
7 116
 
10.3%
] 116
 
10.3%
3 45
 
4.0%
5 45
 
4.0%
, 45
 
4.0%
45
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 322
28.6%
0 277
24.6%
[ 116
 
10.3%
7 116
 
10.3%
] 116
 
10.3%
3 45
 
4.0%
5 45
 
4.0%
, 45
 
4.0%
45
 
4.0%

Hydrogen Standards
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.7%
Missing70290
Missing (%)99.8%
Memory size550.2 KiB
["J2601"]
115 
["J2601-2"]
 
1

Length

Max length11
Median length9
Mean length9.0172414
Min length9

Characters and Unicode

Total characters1046
Distinct characters9
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row["J2601"]
2nd row["J2601"]
3rd row["J2601"]
4th row["J2601"]
5th row["J2601"]

Common Values

ValueCountFrequency (%)
["J2601"] 115
 
0.2%
["J2601-2"] 1
 
< 0.1%
(Missing) 70290
99.8%

Length

2023-08-29T04:26:25.196202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:25.617231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
j2601 115
99.1%
j2601-2 1
 
0.9%

Most occurring characters

ValueCountFrequency (%)
" 232
22.2%
2 117
11.2%
[ 116
11.1%
J 116
11.1%
6 116
11.1%
0 116
11.1%
1 116
11.1%
] 116
11.1%
- 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 465
44.5%
Other Punctuation 232
22.2%
Open Punctuation 116
 
11.1%
Uppercase Letter 116
 
11.1%
Close Punctuation 116
 
11.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 117
25.2%
6 116
24.9%
0 116
24.9%
1 116
24.9%
Other Punctuation
ValueCountFrequency (%)
" 232
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 116
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 116
100.0%
Close Punctuation
ValueCountFrequency (%)
] 116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 930
88.9%
Latin 116
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
" 232
24.9%
2 117
12.6%
[ 116
12.5%
6 116
12.5%
0 116
12.5%
1 116
12.5%
] 116
12.5%
- 1
 
0.1%
Latin
ValueCountFrequency (%)
J 116
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1046
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 232
22.2%
2 117
11.2%
[ 116
11.1%
J 116
11.1%
6 116
11.1%
0 116
11.1%
1 116
11.1%
] 116
11.1%
- 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing68803
Missing (%)97.7%
Memory size550.2 KiB
Q
1155 
T
248 
B
200 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1603
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB
2nd rowQ
3rd rowQ
4th rowB
5th rowQ

Common Values

ValueCountFrequency (%)
Q 1155
 
1.6%
T 248
 
0.4%
B 200
 
0.3%
(Missing) 68803
97.7%

Length

2023-08-29T04:26:26.004562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:26.389424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
q 1155
72.1%
t 248
 
15.5%
b 200
 
12.5%

Most occurring characters

ValueCountFrequency (%)
Q 1155
72.1%
T 248
 
15.5%
B 200
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1603
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Q 1155
72.1%
T 248
 
15.5%
B 200
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1603
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Q 1155
72.1%
T 248
 
15.5%
B 200
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1603
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Q 1155
72.1%
T 248
 
15.5%
B 200
 
12.5%

CNG PSI
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68809
Missing (%)97.7%
Memory size550.2 KiB

CNG Vehicle Class
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)0.2%
Missing68784
Missing (%)97.7%
Memory size550.2 KiB
HD
1331 
MD
254 
LD
 
37

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters3244
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMD
2nd rowMD
3rd rowLD
4th rowHD
5th rowMD

Common Values

ValueCountFrequency (%)
HD 1331
 
1.9%
MD 254
 
0.4%
LD 37
 
0.1%
(Missing) 68784
97.7%

Length

2023-08-29T04:26:26.999748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:27.615121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
hd 1331
82.1%
md 254
 
15.7%
ld 37
 
2.3%

Most occurring characters

ValueCountFrequency (%)
D 1622
50.0%
H 1331
41.0%
M 254
 
7.8%
L 37
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3244
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 1622
50.0%
H 1331
41.0%
M 254
 
7.8%
L 37
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 3244
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 1622
50.0%
H 1331
41.0%
M 254
 
7.8%
L 37
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
D 1622
50.0%
H 1331
41.0%
M 254
 
7.8%
L 37
 
1.1%

LNG Vehicle Class
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing70248
Missing (%)99.8%
Memory size550.2 KiB
HD
158 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters316
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHD
2nd rowHD
3rd rowHD
4th rowHD
5th rowHD

Common Values

ValueCountFrequency (%)
HD 158
 
0.2%
(Missing) 70248
99.8%

Length

2023-08-29T04:26:28.198669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:28.593809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
hd 158
100.0%

Most occurring characters

ValueCountFrequency (%)
H 158
50.0%
D 158
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 316
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 158
50.0%
D 158
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 316
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 158
50.0%
D 158
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 316
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H 158
50.0%
D 158
50.0%
Distinct6
Distinct (%)1.6%
Missing70036
Missing (%)99.5%
Memory size550.2 KiB
SOLAR
252 
NONE
73 
WIND
27 
HYDRO
 
14
WASTEWATER
 
3

Length

Max length10
Median length5
Mean length4.7783784
Min length4

Characters and Unicode

Total characters1768
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowSOLAR
2nd rowSOLAR
3rd rowSOLAR
4th rowWIND
5th rowSOLAR

Common Values

ValueCountFrequency (%)
SOLAR 252
 
0.4%
NONE 73
 
0.1%
WIND 27
 
< 0.1%
HYDRO 14
 
< 0.1%
WASTEWATER 3
 
< 0.1%
LANDFILL 1
 
< 0.1%
(Missing) 70036
99.5%

Length

2023-08-29T04:26:29.022104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T04:26:29.489281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
solar 252
68.1%
none 73
 
19.7%
wind 27
 
7.3%
hydro 14
 
3.8%
wastewater 3
 
0.8%
landfill 1
 
0.3%

Most occurring characters

ValueCountFrequency (%)
O 339
19.2%
R 269
15.2%
A 259
14.6%
S 255
14.4%
L 255
14.4%
N 174
9.8%
E 79
 
4.5%
D 42
 
2.4%
W 33
 
1.9%
I 28
 
1.6%
Other values (4) 35
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1768
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 339
19.2%
R 269
15.2%
A 259
14.6%
S 255
14.4%
L 255
14.4%
N 174
9.8%
E 79
 
4.5%
D 42
 
2.4%
W 33
 
1.9%
I 28
 
1.6%
Other values (4) 35
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1768
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 339
19.2%
R 269
15.2%
A 259
14.6%
S 255
14.4%
L 255
14.4%
N 174
9.8%
E 79
 
4.5%
D 42
 
2.4%
W 33
 
1.9%
I 28
 
1.6%
Other values (4) 35
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1768
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 339
19.2%
R 269
15.2%
A 259
14.6%
S 255
14.4%
L 255
14.4%
N 174
9.8%
E 79
 
4.5%
D 42
 
2.4%
W 33
 
1.9%
I 28
 
1.6%
Other values (4) 35
 
2.0%

Restricted Access
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing16971
Missing (%)24.1%
Memory size550.2 KiB
False
52181 
True
 
1254
(Missing)
16971 
ValueCountFrequency (%)
False 52181
74.1%
True 1254
 
1.8%
(Missing) 16971
 
24.1%
2023-08-29T04:26:30.252306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-08-29T04:25:36.516968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:07.403442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:09.995057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:13.224624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:16.666357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:20.986305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:24.327753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:27.556082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:30.569686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:33.583929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:36.779227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:07.652684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:10.349211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:13.521058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:17.006395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:21.283265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:24.594835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:27.797106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:30.788086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:33.817215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:37.019884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:07.910122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:10.633865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:13.907829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:17.553251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:21.661965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:24.957382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:28.116153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:31.047685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:34.128804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:37.259742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:08.184055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:10.949145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:14.216269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:18.086285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:22.008603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:25.368369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:28.476221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:31.280219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:34.410066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:37.525676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:08.436593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:11.228698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:14.552313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:18.506496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:22.275164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:25.796436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:28.871775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:31.670419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:34.788637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:37.786825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:08.674967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:11.599919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:14.953926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:19.095598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:22.561098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:26.072395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:29.173216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:32.050442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:35.109178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:38.018837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:08.968891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:11.946974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:15.359054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:19.461046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:22.903768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:26.326852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:29.505290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:32.388184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:35.388567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:38.262592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:09.217193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:12.224880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:15.706229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:19.884147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:23.291002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:26.607862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:29.778889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:32.610657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:35.641611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:38.553713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:09.472509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:12.557449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:16.016294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:20.253907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:23.715744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:27.038896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:30.018447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:32.888469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:35.945698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:38.801506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:09.707160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:12.891605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:16.382581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:20.588897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:24.057896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:27.311552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:30.315216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:33.178790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-29T04:25:36.243118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-08-29T04:25:39.886347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-29T04:25:41.164177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-08-29T04:25:44.586663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Fuel Type CodeStation NameStreet AddressIntersection DirectionsCityStateZIPPlus4Station PhoneStatus CodeExpected DateGroups With Access CodeAccess Days TimeCards AcceptedBD BlendsNG Fill Type CodeNG PSIEV Level1 EVSE NumEV Level2 EVSE NumEV DC Fast CountEV Other InfoEV NetworkEV Network WebGeocode StatusLatitudeLongitudeDate Last ConfirmedIDUpdated AtOwner Type CodeFederal Agency IDFederal Agency NameOpen DateHydrogen Status LinkNG Vehicle ClassLPG PrimaryE85 Blender PumpEV Connector TypesCountryIntersection Directions (French)Access Days Time (French)BD Blends (French)Groups With Access Code (French)Hydrogen Is RetailAccess CodeAccess Detail CodeFederal Agency CodeFacility TypeCNG Dispenser NumCNG On-Site Renewable SourceCNG Total Compression CapacityCNG Storage CapacityLNG On-Site Renewable SourceE85 Other Ethanol BlendsEV PricingEV Pricing (French)LPG Nozzle TypesHydrogen PressuresHydrogen StandardsCNG Fill Type CodeCNG PSICNG Vehicle ClassLNG Vehicle ClassEV On-Site Renewable SourceRestricted Access
0CNGSpire - Montgomery Operations Center2951 Chestnut StNaNMontgomeryAL36107NaNNaNENaNPrivateNaNNaNNaNB3600NaNNaNNaNNaNNaNNaN200-932.367916-86.2670212022-06-14172022-06-14 16:22:47 UTCTNaNNaN2010-12-01NaNMDNaNNaNNaNUSNaNNaNNaNPrivéNaNprivateNaNNaNSTANDALONE_STATIONNaNNONENaNNaNNaNNaNNaNNaNNaNNaNNaNB3600MDNaNNaNNaN
1CNGPS Energy - Atlanta340 Whitehall StFrom I-7585 N, exit 91 to Central Ave, left on Memorial, left on Whitehall, and the station is on the leftAtlantaGA30303NaN770-350-3000ENaNPublic - Card key at all times24 hours dailyComdata FleetOne FuelMan Voyager Wright_ExpNaNQ3600NaNNaNNaNNaNNaNNaN200-833.745843-84.3988372021-08-04422022-02-10 19:42:29 UTCPNaNNaN1994-07-15NaNMDNaNNaNNaNUSNaNNaNNaNPublic - Carte-clé en tout tempsNaNpublicKEY_ALWAYSNaNSTANDALONE_STATION1.0NaN30.0NaNNaNNaNNaNNaNNaNNaNNaNQ3600MDNaNNaNFalse
2CNGMetropolitan Atlanta Rapid Transit Authority2424 Piedmont Rd NENaNAtlantaGA30324NaNNaNENaNPrivate - Government onlyNaNNaNNaNQ3000NaNNaNNaNNaNNaNNaN200-833.821911-84.3674612021-08-04452022-02-10 19:42:29 UTCLGNaNNaN1996-12-15NaNLDNaNNaNNaNUSNaNNaNNaNPrivé - Réservé au gouvernementNaNprivateGOVERNMENTNaNFLEET_GARAGENaNNaN30.0NaNNaNNaNNaNNaNNaNNaNNaNQ3000LDNaNNaNNaN
3CNGUnited Parcel Service270 Marvin Miller DrNaNAtlantaGA30336NaNNaNENaNPrivateNaNNaNNaNB3600NaNNaNNaNNaNNaNNaN200-933.760256-84.5438222022-06-14642022-06-14 16:22:47 UTCPNaNNaN1997-01-01NaNHDNaNNaNNaNUSNaNNaNNaNPrivéNaNprivateNaNNaNSTANDALONE_STATIONNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNB3600HDNaNNaNNaN
4CNGArkansas Oklahoma Gas Corp2100 S Waldron RdNaNFort SmithAR72903NaN479-783-3188ENaNPublic - Credit card at all times24 hours dailyFuelMan M V Wright_ExpNaNQ3600NaNNaNNaNNaNNaNNaN200-935.362213-94.3753382022-06-14732022-06-14 16:22:47 UTCTNaNNaN1997-01-01NaNMDNaNNaNNaNUSNaNNaNNaNPublic - Carte de crédit en tout tempsNaNpublicCREDIT_CARD_ALWAYSNaNUTILITY1.0NONE250.057855.0NaNNaNNaNNaNNaNNaNNaNQ3600MDNaNNaNFalse
5CNGClean Energy - Logan International Airport1000 Cottage St ExtFrom Route 1, take the first exit after Callahan Tunnel. Located near the Massachusetts State Police Troop F building on Service Rd.East BostonMA2128NaN866-809-4869ENaNPublic - Credit card at all times24 hours daily; call 866-809-4869 for Clean Energy cardA CleanEnergy Comdata D FuelMan M V Voyager Wright_ExpNaNQ3000 3600NaNNaNNaNNaNNaNNaNGPS42.374706-71.0265492021-08-04812022-02-10 19:42:29 UTCSGNaNNaN1996-11-15NaNMDNaNNaNNaNUSNaNNaNNaNPublic - Carte de crédit en tout tempsNaNpublicCREDIT_CARD_ALWAYSNaNAIRPORT4.0NONE850.0NaNNaNNaNNaNNaNNaNNaNNaNQ3000 3600MDNaNNaNFalse
6CNGClean Energy - Everett - National Grid16 Rover StRt 16, exit to Rt 99, to Dexter St to Rover. Or Rt 99 to Robin St, to Rover StEverettMA2149NaN866-809-4869ENaNPublic - Credit card at all times24 hours daily; call 866-809-4869 for Clean Energy cardCleanEnergy D FleetOne FuelMan M V Voyager Wright_ExpNaNQ3000 3600NaNNaNNaNNaNNaNNaN200-842.393167-71.0643522021-05-06842022-02-10 19:42:29 UTCTNaNNaN1996-11-15NaNHDNaNNaNNaNUSNaNNaNNaNPublic - Carte de crédit en tout tempsNaNpublicCREDIT_CARD_ALWAYSNaNSTANDALONE_STATION1.0NONE425.0NaNNaNNaNNaNNaNNaNNaNNaNQ3000 3600HDNaNNaNFalse
7CNGClean Energy - Greenpoint - National Grid287 Maspeth AveI-278/Brooklyn Queens Expy, exit onto Vandervoort Ave S, left onto Maspeth Ave, and the station is on the leftBrooklynNY11211NaN866-809-4869ENaNPublic - Credit card at all times24 hours daily; call 866-809-4869 for Clean Energy cardCleanEnergy D FuelMan M V Voyager Wright_ExpNaNQ3000 3600NaNNaNNaNNaNNaNNaN200-840.718037-73.9323092021-05-061082022-02-10 19:42:29 UTCTNaNNaN2016-07-15NaNHDNaNNaNNaNUSNaNNaNNaNPublic - Carte de crédit en tout tempsNaNpublicCREDIT_CARD_ALWAYSNaNUTILITY1.0NONE1200.0NaNNaNNaNNaNNaNNaNNaNNaNQ3000 3600HDNaNNaNFalse
8CNGCanarsie - National Grid8424 Ditmas AveFrom Shore Pkwy, take Rockaway Pkwy N, left onto Ditmas Ave, and station is on the leftBrooklynNY11236NaN866-809-4869ENaNPublic - Credit card at all times24 hours daily; call 866-809-4869 for Clean Energy card; Also accepts OGSCleanEnergy D FleetOne FuelMan M Proprietor V Voyager Wright_ExpNaNB3000 3600NaNNaNNaNNaNNaNNaN200-840.645540-73.9183442021-09-101122022-02-10 19:42:29 UTCTNaNNaN1988-01-15NaNMDNaNNaNNaNUSNaNNaNNaNPublic - Carte de crédit en tout tempsNaNpublicCREDIT_CARD_ALWAYSNaNUTILITY1.0NONE525.0NaNNaNNaNNaNNaNNaNNaNNaNB3000 3600MDNaNNaNFalse
9CNGCon Edison - W 29th St Service Center281 11th AveIn Manhattan, W 29th Street and 12th Avenue.New YorkNY10001NaN212-643-3054ENaNPublic - Card key at all times24 hours daily; call 718-204-4100 to arrange for card keyNaNNaNQ3600NaNNaNNaNNaNNaNNaN200-940.752903-74.0058312022-06-141242022-06-14 16:22:47 UTCTNaNNaN2014-05-01NaNMDNaNNaNNaNUSNaNNaNNaNPublic - Carte-clé en tout tempsNaNpublicKEY_ALWAYSNaNUTILITY1.0NaN300.0NaNNaNNaNNaNNaNNaNNaNNaNQ3600MDNaNNaNFalse
Fuel Type CodeStation NameStreet AddressIntersection DirectionsCityStateZIPPlus4Station PhoneStatus CodeExpected DateGroups With Access CodeAccess Days TimeCards AcceptedBD BlendsNG Fill Type CodeNG PSIEV Level1 EVSE NumEV Level2 EVSE NumEV DC Fast CountEV Other InfoEV NetworkEV Network WebGeocode StatusLatitudeLongitudeDate Last ConfirmedIDUpdated AtOwner Type CodeFederal Agency IDFederal Agency NameOpen DateHydrogen Status LinkNG Vehicle ClassLPG PrimaryE85 Blender PumpEV Connector TypesCountryIntersection Directions (French)Access Days Time (French)BD Blends (French)Groups With Access Code (French)Hydrogen Is RetailAccess CodeAccess Detail CodeFederal Agency CodeFacility TypeCNG Dispenser NumCNG On-Site Renewable SourceCNG Total Compression CapacityCNG Storage CapacityLNG On-Site Renewable SourceE85 Other Ethanol BlendsEV PricingEV Pricing (French)LPG Nozzle TypesHydrogen PressuresHydrogen StandardsCNG Fill Type CodeCNG PSICNG Vehicle ClassLNG Vehicle ClassEV On-Site Renewable SourceRestricted Access
70396ELECEsquimalt Gorge Park-1070 Tillicum RoadNaNEsquimaltBCV9A 2A3NaN888-356-8911ENaNPublic24 hours dailyNaNNaNNaNNaNNaN2.0NaNNaNFLOhttps://flo.ca/GPS48.446013-123.4049442022-07-252243692022-07-25 01:37:03 UTCNaNNaNNaN2022-07-23NaNNaNNaNNaNJ1772CANaNAccessible 24 heures par jourNaNPublicNaNpublicNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70397ELECLatitude - 5265 Natorp5265 Natrop BlvdNaNMasonOH45040NaN888-356-8911ENaNPublic24 hours dailyNaNNaNNaNNaNNaN2.0NaNNaNFLOhttps://flo.ca/GPS39.299806-84.3201392022-07-252243712022-07-25 01:48:14 UTCNaNNaNNaN2022-07-23NaNNaNNaNNaNJ1772USNaNNaNNaNPublicNaNpublicNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70398ELEC8100 Cote Saint-Luc Road8100 Cote Saint-Luc RoadNaNSaint-LucQCH4W 3C3NaN855-999-8378ENaNPublic24 hours dailyNaNNaNNaNNaNNaN1.0NaNNaNCircuit électriquehttps://lecircuitelectrique.com/GPS45.458458-73.6642262022-07-252243732022-07-25 01:50:26 UTCNaNNaNNaN2022-07-23NaNNaNNaNNaNJ1772CANaNAccessible 24 heures par jourNaNPublicNaNpublicNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70399ELECPeoria Development and Community Services Building9875 N. 85th AveNaNPeoriaAZ85345NaN888-998-2546ENaNPublicMON: 24 hours | TUE: 24 hours | WED: 24 hours | THU: 24 hours | FRI: 24 hours | SAT: 24 hours | SUN: 24 hoursNaNNaNNaNNaNNaN2.0NaNNaNBlink Networkhttp://www.blinkcharging.com/GPS33.574215-112.2420492022-07-242243742022-07-24 22:55:19 UTCNaNNaNNaN2022-07-23NaNNaNNaNNaNJ1772USNaNNaNNaNPublicNaNpublicNaNNaNNaNNaNNaNNaNNaNNaNNaNLevel 2: $0.49 per kWhNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70400ELECBlink Charging - Tempe2404 W 14th St.NaNTempeAZ85281NaN888-998-2546ENaNPrivateMON: 24 hours | TUE: 24 hours | WED: 24 hours | THU: 24 hours | FRI: 24 hours | SAT: 24 hours | SUN: 24 hoursNaNNaNNaNNaNNaN6.0NaNNaNBlink Networkhttp://www.blinkcharging.com/GPS33.413918-111.9748392022-07-242243752022-07-24 22:55:19 UTCNaNNaNNaN2022-07-23NaNNaNNaNNaNJ1772USNaNNaNNaNPrivéNaNprivateNaNNaNNaNNaNNaNNaNNaNNaNNaNLevel 2: $0.49 per kWhNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70401ELECSCHLITZ PARK SCHLITZ PARK1555 N River Center DrNaNMilwaukeeWI53212NaN888-758-4389ENaNPublic24 hours dailyNaNNaNNaNNaNNaN2.0NaNNaNChargePoint Networkhttp://www.chargepoint.com/GPS43.050637-87.9100152022-07-252243762022-07-25 00:58:13 UTCNaNNaNNaN2022-07-24NaNNaNNaNNaNJ1772USNaNNaNNaNPublicNaNpublicNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70402ELECNEXUS EAST STATION 2720 Airport BlvdNaNAustinTX78702NaN888-758-4389ENaNPublic24 hours dailyNaNNaNNaNNaNNaN2.0NaNNaNChargePoint Networkhttp://www.chargepoint.com/GPS30.252438-97.6944272022-07-252243772022-07-25 01:22:29 UTCNaNNaNNaN2022-07-24NaNNaNNaNNaNJ1772USNaNNaNNaNPublicNaNpublicNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70403ELECRaley's6119 Horseshoe Bar RdNaNLoomisCA95650NaN877-455-3833ENaNPublic24 hours dailyNaNNaNNaNNaNNaNNaN2.0NaNeVgo Networkhttps://www.evgo.com/GPS38.817727-121.1887512022-07-252243802022-07-25 01:30:43 UTCNaNNaNNaN2022-07-25NaNNaNNaNNaNCHADEMO J1772COMBOUSNaNNaNNaNPublicNaNpublicNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70404ELEC13601 Glenoaks blvd13601 Glenoaks blvdNaNLos AngelesCA91342NaN888-356-8911ENaNPublic24 hours dailyNaNNaNNaNNaNNaN1.0NaNNaNFLOhttps://flo.ca/GPS34.318879-118.4644782022-07-252243812022-07-25 01:48:14 UTCNaNNaNNaN2022-07-25NaNNaNNaNNaNJ1772CANaNAccessible 24 heures par jourNaNPublicNaNpublicNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70405ELEC6723 Van Nuys blvd6723 Van Nuys BlvdNaNLos AngelesCA91405NaN888-356-8911ENaNPublic24 hours dailyNaNNaNNaNNaNNaN1.0NaNNaNFLOhttps://flo.ca/GPS34.192599-118.4488242022-07-252243822022-07-25 01:48:14 UTCNaNNaNNaN2022-07-25NaNNaNNaNNaNJ1772CANaNAccessible 24 heures par jourNaNPublicNaNpublicNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN